Predict market fluctuations based on the TSI and the sentiment of financial video news sites via machine learning

Conference paper

Alzazah, F., Gao, X. and Cheng, X. 2023. Predict market fluctuations based on the TSI and the sentiment of financial video news sites via machine learning. 15th International Conference on Computer and Automation Engineering. Sydney, Australia 03 - 05 Mar 2023 IEEE. https://doi.org/10.1109/iccae56788.2023.10111493
TypeConference paper
TitlePredict market fluctuations based on the TSI and the sentiment of financial video news sites via machine learning
AuthorsAlzazah, F., Gao, X. and Cheng, X.
Abstract

Scientists have long been interested in forecasting stock market fluctuations. Traditional data like financial textual news, stock prices, and comments are simply no longer sufficient because they don't provide a comprehensive picture. In this study, the efficacy of using financial video news stories versus the use of conventional text news stories to forecast the stock market is examined. We used the Granger causality test to evaluate the robustness of the causal connection between share prices, text news sentiment, video news sentiments, and the Twitter sentiment index.Several models for sentiment analysis of S&P 500 stock were assessed using LR, SVM, LSTM, ATT-LSTM, and CNN models. This study is distinctive because it compares the use of financial video news stories, conventional text news stories, and the Twitter Sentiment Index to forecast stock market movements. The experimental results suggest that there is a stronger causal connection between video news sentiment and stock market fluctuation compared to conventional text news sentiments. The result shows that we can more accurately predict market changes using video news than we can with traditional news.

Sustainable Development Goals3 Good health and well-being
Middlesex University ThemeHealth & Wellbeing
Conference15th International Conference on Computer and Automation Engineering
Proceedings Title2023 15th International Conference on Computer and Automation Engineering, ICCAE 2023
ISSN2154-4352
Electronic2154-4360
ISBN
Electronic9798350396225
Electronic9798350396218
Paperback9798350396232
PublisherIEEE
Publication dates
Print03 Mar 2023
Online03 May 2023
Publication process dates
Accepted18 Jan 2023
Deposited29 Apr 2026
Output statusPublished
Accepted author manuscript
File Access Level
Open
Copyright Statement

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Digital Object Identifier (DOI)https://doi.org/10.1109/iccae56788.2023.10111493
Scopus EID2-s2.0-85159591320
Web address (URL) of conference proceedingshttps://doi.org/10.1109/ICCAE56788.2023
LanguageEnglish
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Gao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X. 2022. Detection of human papillomavirus (HPV) from super resolution microscopic images applying an explainable deep learning network. SPIE Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging. San Diego, USA 20 - 22 Feb 2022 Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2624423
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Gao, X., Taylor, S., Pang, W., Lu, X. and Braden, B. 2022. Early detection of oesophageal cancer through colour contrast enhancement for data augmentation. SPIE Medical Imaging: Computer-Aided Diagnosis. San Diego, USA 21 - 24 Feb 2022 Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2611409
Gold-viral particle identification by deep learning in wide-field photon scattering parametric images
Zhao, H., Ni, B., Jin, X., Zhang, H., Hou, J., Hou, L., Marsh, J., Dong, L., Li, S., Gao, X., Shi, D., Liu, X. and Xiong, J. 2022. Gold-viral particle identification by deep learning in wide-field photon scattering parametric images. Applied Optics. 61 (2), pp. 546-553. https://doi.org/10.1364/AO.445953
CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model
Ullah, F., Naeem, M., Naeem, H., Cheng, X. and Alazab, M. 2022. CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model. International Journal of Intelligent Systems. 37 (9), pp. 5768-5795. https://doi.org/10.1002/int.22813
Editorial: Security of cloud service for the manufacturing industry
Cheng, X., Liu, Z. and Ning, Y. 2022. Editorial: Security of cloud service for the manufacturing industry. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4369
Signal denoising of viral particle in wide-field photon scattering parametric images using deep learning
Zhao, H., Ni, B., Liu, W., Jin, X., Zhang, H., Gao, X., Wen, S., Shi, D., Dong, L., Xiong, J. and Liu, X. 2022. Signal denoising of viral particle in wide-field photon scattering parametric images using deep learning. Optics Communications. 503. https://doi.org/10.1016/j.optcom.2021.127463
MobiScan: an enhanced invisible screen‐camera communication system for IoT applications
Zhang, X., Liu, J., Ba, Z., Tao, Y. and Cheng, X. 2022. MobiScan: an enhanced invisible screen‐camera communication system for IoT applications. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4151
Secure smart contracts for cloud-based manufacturing using Ethereum blockchain
Kumar, A., Abhishek, K., Nerurkar, P., Ghalib, M., Shankar, A. and Cheng, X. 2022. Secure smart contracts for cloud-based manufacturing using Ethereum blockchain. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4129
Artificial intelligence in endoscopy: the challenges and future directions
Gao, X. and Braden, B. 2021. Artificial intelligence in endoscopy: the challenges and future directions. Artifical Intelligence in Gastrointestinal Endoscopy. 2 (4), pp. 117-126. https://doi.org/10.37126/aige.v2.i4.117
Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN)
Heenaye-Mamode Khan,, M., Boodoo-Jahangeer, N., Dullull, W., Nathire, S., Gao, X., Sinha, G.R. and Nagwanshi, K.K. 2021. Multi- class classification of breast cancer abnormalities using Deep Convolutional Neural Network (CNN). PLoS ONE. 16 (8). https://doi.org/10.1371/journal.pone.0256500
COVID-CBR: a deep learning architecture featuring case-based reasoning for classification of COVID-19 from chest x-ray images
Gao, X. and Gao, A. 2021. COVID-CBR: a deep learning architecture featuring case-based reasoning for classification of COVID-19 from chest x-ray images. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Virtual online 13 - 16 Dec 2021 IEEE. pp. 1319-1324 https://doi.org/10.1109/ICMLA52953.2021.00214
Evaluation of GAN architectures for visualisation of HPV viruses from microscopic images
Gao, X., Wen, S., Li, D., Liu, W., Xiong, J., Xu, B., Liu, J., Zhang, H. and Liu, X. 2021. Evaluation of GAN architectures for visualisation of HPV viruses from microscopic images. 2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA). Virtual online 13 - 16 Dec 2021 IEEE. pp. 829-833 https://doi.org/10.1109/ICMLA52953.2021.00137
Characterization of deep sub-wavelength nanowells by imaging the photon state scattering spectra
Liu, W., Liu, X. and Gao, X. 2021. Characterization of deep sub-wavelength nanowells by imaging the photon state scattering spectra. Optics Express. 29 (2), pp. 1221-1231. https://doi.org/10.1364/OE.413942
Power grid-oriented cascading failure vulnerability identifying method based on wireless sensors
Li, S., Chen, Y., Wu, X., Cheng, X. and Tian, Z. 2021. Power grid-oriented cascading failure vulnerability identifying method based on wireless sensors. Journal of Sensors. 2021, pp. 1-12. https://doi.org/10.1155/2021/8820413
Task bundling in worker-centric mobile crowdsensing
Zhao, T., Yang, Y., Wang, E., Mumtaz, S. and Cheng, X. 2021. Task bundling in worker-centric mobile crowdsensing. International Journal of Intelligent Systems. 36 (9), pp. 4936-4961. https://doi.org/10.1002/int.22497
Secure and energy-efficient smart building architecture with emerging technology IoT
Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X. and Singh, P. 2021. Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications. 176, pp. 207-217. https://doi.org/10.1016/j.comcom.2021.06.003
Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment
Narayanan, S., Baby, C., Perumal, B., Bhatt, R., Cheng, X., Ghalib, M. and Shankar, A. 2021. Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment. International Journal of Intelligent Systems. 36 (8), pp. 4280-4267. https://doi.org/10.1002/int.22459
[Retracted] PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation
Wang, S., Zhang, Y., Cheng, X., Zhang, X. and Zhang, Y. 2021. [Retracted] PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an Explainable Diagnosis of COVID-19 with Multiple-Way Data Augmentation. Computational and Mathematical Methods in Medicine. 2021, pp. 1-18. https://doi.org/10.1155/2021/6633755
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Ali, S., Dmitrieva, M., Ghatwary, N., Bano, S., Polat, G., Temizel, A., Krenzer, A., Hekalo, A., Guo, Y., Matuszewski, B., Gridach, M., Voiculescu, I., Yoganand, V., Chavan, A., Raj, A., Nguyen, N., Tran, D., Huynh, L., Boutry, N., Rezvy, S., Chen, H., Choi, Y., Subramanian, A., Balasubramanian, V., Gao, X., Hu, H., Liao, Y., Stoyanov, D., Daul, C., Realdon, S., Cannizzaro, R., Lamarque, D., Tran-Nguyen, T., Bailey, A., Braden, B., East, J. and Rittscher, J. 2021. Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy. Medical Image Analysis. 70. https://doi.org/10.1016/j.media.2021.102002
ShadowFPE: new encrypted web application solution based on shadow DOM
Guo, X., Huang, Y., Ye, J., Yin, S., Li, M., Li, Z., Yiu, S. and Cheng, X. 2021. ShadowFPE: new encrypted web application solution based on shadow DOM. Mobile Networks and Applications. 26 (4), pp. 1733-1746. https://doi.org/10.1007/s11036-019-01509-y
Learning context-aware outfit recommendation
Abugabah, A., Cheng, X. and Wang, J. 2020. Learning context-aware outfit recommendation. Symmetry. 12 (6), pp. 1-13. https://doi.org/10.3390/sym12060873
Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm
Liu, W., Huang, Y., Ye, Z., Cai, W., Yang, S., Cheng, X. and Frank, I. 2020. Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm. Applied Sciences. 10 (9). https://doi.org/10.3390/app10093225
XOR multiplexing technique for nanocomputers
Yu, L., Diao, M., Chen, X. and Cheng, X. 2020. XOR multiplexing technique for nanocomputers. Applied Sciences. 10 (8). https://doi.org/10.3390/app10082825
Adaptive dynamic disturbance strategy for differential evolution algorithm
Wang, T., Wu, K., Du, T. and Cheng, X. 2020. Adaptive dynamic disturbance strategy for differential evolution algorithm. Applied Sciences. 10 (6). https://doi.org/10.3390/app10061972
Hybridization of cognitive computing for food services
Zhang, X., Yang, S., Srivastava, G., Chen, M. and Cheng, X. 2020. Hybridization of cognitive computing for food services. Applied Soft Computing. 89. https://doi.org/10.1016/j.asoc.2019.106051
Facial landmark detection via attention-adaptive deep network
Sadiq, M., Shi, D., Guo, M. and Cheng, X. 2019. Facial landmark detection via attention-adaptive deep network. IEEE Access. 7, pp. 181041-181050. https://doi.org/10.1109/ACCESS.2019.2955156
Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha
Yhang, X., Mohanty, S., Parida, A., Pani, S., Dong, B. and Cheng, X. 2020. Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha. IEEE Access. 8, pp. 30223-30233. https://doi.org/10.1109/ACCESS.2020.2972435
A sparse Bayesian learning method for structural equation model-based gene regulatory network inference
Li, Y., Liu, D., Chu, J., Zhu, Y., Liu, J. and Cheng, X. 2020. A sparse Bayesian learning method for structural equation model-based gene regulatory network inference. IEEE Access. 8, pp. 40067-40080. https://doi.org/10.1109/ACCESS.2020.2976743
Transfer learning for endoscopy disease detection and segmentation with mask-RCNN benchmark architecture
Rezvy, S., Zebin, T., Pang, W., Taylor, S. and Gao, X. 2020. Transfer learning for endoscopy disease detection and segmentation with mask-RCNN benchmark architecture. 2nd International Workshop and Challenge on Computer Vision in Endoscopy. Iowa City, United States 03 Apr 2020 pp. 68-72
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Ali, S., Zhou, F., Braden, B., Bailey, A., Yang, S., Cheng, G., Zhang, P., Li, X., Kayser, M., Soberanis-Mukul, R., Albarqouni, S., Wang, X., Wang, C., Watanabe, S., Oksuz, I., Ning, Q., Yang, S., Khan, M., Gao, X., Realdon, S., Loshchenov, M., Schnabel, J., East, J., Wagnieres, G., Loschenov, V., Grisan, E., Daul, C., Blondel, W. and Rittscher, J. 2020. An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific Reports. 10 (1), pp. 1-15. https://doi.org/10.1038/s41598-020-59413-5
An enhanced deep learning architecture for classification of Tuberculosis types from CT lung images
Gao, X., Comley, R. and Khan, M. 2020. An enhanced deep learning architecture for classification of Tuberculosis types from CT lung images. ICIP 2020: 27th IEEE International Conference on Image Processing. Abu Dhabi, Unites Arab Emirates (Virtual Conference) 25 - 28 Oct 2020 IEEE. pp. 2486-2490 https://doi.org/10.1109/ICIP40778.2020.9190815
Reliability analysis of an air traffic network: from network structure to transport function
Li, S., Zhang, Z. and Cheng, X. 2020. Reliability analysis of an air traffic network: from network structure to transport function. Applied Sciences. 10 (9). https://doi.org/10.3390/app10093168
Fine-grained action recognition by motion saliency and mid-level patches
Liu, F., Zhao, L., Cheng, X., Dai, Q., Shi, X. and Qiao, J. 2020. Fine-grained action recognition by motion saliency and mid-level patches. Applied Sciences. 10 (8). https://doi.org/10.3390/app10082811
Case-based reasoning of a deep learning network for prediction of early stage of oesophageal cancer
Gao, X., Braden, B., Zhang, L., Taylor, S., Pang, W. and Petridis, M. 2020. Case-based reasoning of a deep learning network for prediction of early stage of oesophageal cancer. 24th UK Symposium on Case-Based Reasoning (UKCBR 2019). Cambridge, UK 17 Dec 2019 BCS SGAI: The Specialist Group on Artificial Intelligence. pp. 1-12
A game theoretic analysis of resource mining in blockchain
Singh, R., Dwivedi, A., Srivastava, G., Wisznieska-Mayszkiel, A. and Cheng, X. 2020. A game theoretic analysis of resource mining in blockchain. Cluster Computing. 23 (3), pp. 2035-2046. https://doi.org/10.1007/s10586-020-03046-w
Unbalanced private set intersection cardinality protocol with low communication cost
Lv, S., Ye, J., Yin, S. and Cheng, X. 2020. Unbalanced private set intersection cardinality protocol with low communication cost. Future Generation Computer Systems. 102, pp. 1054-1061. https://doi.org/10.1016/j.future.2019.09.022
Imbalanced big data classification based on virtual reality in cloud computing
Xie, W. and Cheng, X. 2020. Imbalanced big data classification based on virtual reality in cloud computing. Multimedia Tools and Applications. 79 (23-24), pp. 16403-16420. https://doi.org/10.1007/s11042-019-7317-x
Analysis of tuberculosis severity levels from CT pulmonary images based on enhanced residual deep learning architecture
Gao, X., James-Reynolds, C. and Currie, E. 2020. Analysis of tuberculosis severity levels from CT pulmonary images based on enhanced residual deep learning architecture. Neurocomputing. 392, pp. 233-244. https://doi.org/10.1016/j.neucom.2018.12.086
Micro-distortion detection of lidar scanning signals based on geometric analysis
Liu, S., Chen, X., Li, Y. and Cheng, X. 2019. Micro-distortion detection of lidar scanning signals based on geometric analysis. Symmetry. 11 (12), pp. 2-13. https://doi.org/10.3390/sym11121471
Verifying cryptographic protocols
Ma, X. and Cheng, X. 2005. Verifying cryptographic protocols. IEEE Journal of Intelligent Cybernetic Systems.
Verifying security protocols by knowledge analysis
Ma, X. and Cheng, X. 2008. Verifying security protocols by knowledge analysis. International Journal of Security and Networks. 3 (3), pp. 183-192. https://doi.org/10.1504/IJSN.2008.020092
A security design for cloud computing: an implementation of an on premises authentication with Kerberos and IPSec within a network
Umar, M. and Cheng, X. 2012. A security design for cloud computing: an implementation of an on premises authentication with Kerberos and IPSec within a network. International Journal of Advanced Research in Computer Science. 3 (1), pp. 10-16. https://doi.org/10.26483/ijarcs.v3i1.6040
Comparative experiments on resource discovery in P2P networks
Gautam, S. and Cheng, X. 2014. Comparative experiments on resource discovery in P2P networks. Journal of Next Generation Information Technology. 5 (1), pp. 89-98.
Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface
Men, J., Xu, G., Han, Z., Sun, Z., Zhou, X., Lian, W. and Cheng, X. 2019. Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface. IEEE Access. 7, pp. 103751-103759. https://doi.org/10.1109/ACCESS.2019.2931061
Patch-based deep learning approaches for artefact detection of endoscopic images
Gao, X. and Qian, Y. 2019. Patch-based deep learning approaches for artefact detection of endoscopic images. Endoscopic artefact detection challenge 2019 (EAD2019). Venice, Italy 08 Apr 2019 CEUR Workshop Proceedings (CEUR-WS.org).
Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs
Shi, F., Chen, Z. and Cheng, X. 2020. Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs. IEEE Access. 8, pp. 2447-2454. https://doi.org/10.1109/ACCESS.2019.2923059
Vulnerabilities and limitations of MQTT protocol used between IoT devices
Dinculeană, D. and Cheng, X. 2019. Vulnerabilities and limitations of MQTT protocol used between IoT devices. Applied Sciences. 9 (5). https://doi.org/10.3390/app9050848
Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network
Xie, X., Zhang, Z., Wang, J. and Cheng, X. 2019. Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network. Journal on Communications. 40 (8), pp. 143-150. https://doi.org/10.11959/j.issn.1000-436x.2019172
An authentication scheme to defend against UDP DrDoS attacks in 5G networks
Huang, H., Hu, L., Chu, J. and Cheng, X. 2019. An authentication scheme to defend against UDP DrDoS attacks in 5G networks. IEEE Access. 7, pp. 175970-175979. https://doi.org/10.1109/ACCESS.2019.2957565
Incremental association rule mining based on matrix compression for edge computing
Zhou, D., Ouyang, M., Kuang, Z., Li, Z., Zhou, J. and Cheng, X. 2019. Incremental association rule mining based on matrix compression for edge computing. IEEE Access. 7, pp. 1730444-173053. https://doi.org/10.1109/ACCESS.2019.2956823
Towards real-time detection of squamous pre-cancers from oesophageal endoscopic videos
Gao, X., Braden, B., Taylor, S. and Pang, W. 2019. Towards real-time detection of squamous pre-cancers from oesophageal endoscopic videos. ICMLA 2019. Boca Raton, Florida, USA 16 - 19 Dec 2019 IEEE. pp. 1606-1612 https://doi.org/10.1109/ICMLA.2019.00264
Introduction of key problems in long-distance learning and training
Liu, S., Li, Z., Zhang, Y. and Cheng, X. 2019. Introduction of key problems in long-distance learning and training. Mobile Networks and Applications. 24 (1), pp. 1-4. https://doi.org/10.1007/s11036-018-1136-6
Data provenance with retention of reference relations
Wang, C., Yang, L., Wu, Y., Wu, Y., Cheng, X., Li, Z. and Liu, Z. 2018. Data provenance with retention of reference relations. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2876879
Platform of quality evaluation system for multimedia video communication based NS2
Yu, G., Cheng, X. and Xu, J. 2018. Platform of quality evaluation system for multimedia video communication based NS2. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-018-1164-x
Research on trust model in container-based cloud service
Xie, X., Yuan, T., Zhou, X. and Cheng, X. 2018. Research on trust model in container-based cloud service. Computers, Materials and Continua. 56 (2), pp. 273-283. https://doi.org/10.3970/cmc.2018.03587
Analysing TB severity levels with an enhanced deep residual learning– depth-resnet
Gao, X., James-Reynolds, C. and Currie, E. 2018. Analysing TB severity levels with an enhanced deep residual learning– depth-resnet. Cappellato, L., Ferro, N., Nie, J-Y. and Soulier, L. (ed.) CLEF 2018 Conference and Labs of the Evaluation Forum - ImageCLEF-Multimedia Retrieval in CLEF. Avignon, France 10 - 14 Sep 2018 CEUR Workshop Proceedings (CEUR-WS.org).
Introduction of recent advanced hybrid information processing
Liu, S., Li, Z., Cheng, X. and Lin, Y. 2018. Introduction of recent advanced hybrid information processing. Mobile Networks and Applications. 23 (4), pp. 673-676. https://doi.org/10.1007/s11036-018-1013-3
Accurate Sybil attack detection based on fine-grained physical channel information
Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z. and Cheng, X. 2018. Accurate Sybil attack detection based on fine-grained physical channel information. Sensors. 18 (3). https://doi.org/10.3390/s18030878
Channel state information-based detection of Sybil attacks in wireless networks
Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z. and Cheng, X. 2018. Channel state information-based detection of Sybil attacks in wireless networks. Journal of Internet Services and Information Security. 8 (1), pp. 2-17. https://doi.org/10.22667/JISIS.2018.02.28.002
DivORAM: Towards a practical oblivious RAM with variable block size
Liu, Z., Huang, Y., Li, J., Cheng, X. and Shen, C. 2018. DivORAM: Towards a practical oblivious RAM with variable block size. Information Sciences. 447, pp. 1-11. https://doi.org/10.1016/j.ins.2018.02.071
M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices
Gao, C., Lv, S., Wei, Y., Wang, Z., Liu, Z. and Cheng, X. 2018. M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices. IEEE Access. 6, pp. 38860-38869. https://doi.org/10.1109/ACCESS.2018.2852329
A distributed anomaly detection system for in-vehicle network using HTM
Wang, C., Zhao, Z., Gong, L., Zhu, L., Liu, Z. and Cheng, X. 2018. A distributed anomaly detection system for in-vehicle network using HTM. IEEE Access. 6, pp. 9091-9098. https://doi.org/10.1109/ACCESS.2018.2799210
Prediction of multidrug-resistant TB from CT pulmonary images based on deep learning techniques
Gao, X. and Qian, Y. 2018. Prediction of multidrug-resistant TB from CT pulmonary images based on deep learning techniques. Molecular Pharmaceutics. 15 (10), pp. 4326-4335. https://doi.org/10.1021/acs.molpharmaceut.7b00875
Crime pattern recognition based on high-performance computing
Eissa, A., Cheng, X. and Petridis, M. 2018. Crime pattern recognition based on high-performance computing. 2017 International Conference Next Generation Community Policing. Heraklion, Crete, Greece 25 - 27 Oct 2017
Segmentation of brain lesions from CT images based on deep learning techniques
Gao, X. and Qian, Y. 2018. Segmentation of brain lesions from CT images based on deep learning techniques. Gimi, B. and Krol, A. (ed.) SPIE Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging. Houston, Texas, United States 10 - 15 Feb 2018 Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.2286844
A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface
Liu, S., Pan, Z. and Cheng, X. 2017. A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals. 25 (04), pp. 1740004-1-11. https://doi.org/10.1142/s0218348x17400047
Editorial: Recent advances of content understanding in image and multimedia [Editorial]
Liu, S., Cheng, X. and Min, G. 2017. Editorial: Recent advances of content understanding in image and multimedia [Editorial]. Recent Patents on Computer Science. 10 (1), pp. 2-5. https://doi.org/10.2174/221327591001170808093310
Application of deep learning neural network for classification of TB lung CT images based on patches
Gao, X. and Qian, Y. 2017. Application of deep learning neural network for classification of TB lung CT images based on patches. ImageCLEF / LifeCLEF - Multimedia Retrieval in CLEF: CLEF 2017: Conference and Labs of the Evaluation Forum. Dublin, Ireland 11 - 14 Sep 2017 CEUR Workshop Proceedings (CEUR-WS.org).
A fused deep learning architecture for viewpoint classification of echocardiography
Gao, X., Li, W., Loomes, M. and Wang, L. 2017. A fused deep learning architecture for viewpoint classification of echocardiography. Information Fusion. 36, pp. 103-113. https://doi.org/10.1016/j.inffus.2016.11.007
Classification of CT brain images based on deep learning networks
Gao, X., Hui, R. and Tian, Z. 2017. Classification of CT brain images based on deep learning networks. Computer Methods and Programs in Biomedicine. 138 (2017), pp. 49-56. https://doi.org/10.1016/j.cmpb.2016.10.007
Degradation and encryption for outsourced PNG images in cloud storage
Wang, Y., Du, J., Cheng, X., Liu, Z. and Lin, K. 2016. Degradation and encryption for outsourced PNG images in cloud storage. International Journal of Grid and Utility Computing. 7 (1), pp. 22-28. https://doi.org/10.1504/IJGUC.2016.073773
Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud
Xie, X., Liu, R., Cheng, X., Hu, X. and Ni, J. 2016. Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud. Intelligent Automation & Soft Computing: An International Journal . 22 (4), pp. 561-566.
A deep learning based approach to classification of CT brain images
Gao, X. and Hui, R. 2016. A deep learning based approach to classification of CT brain images. SAI Computing Conference 2016. London, UK 13 - 15 Jul 2016 IEEE. https://doi.org/10.1109/sai.2016.7555958
A new approach to image enhancement for the visually impaired
Gao, X. and Loomes, M. 2016. A new approach to image enhancement for the visually impaired. IS&T International Symposium on Electronic Imaging 2016 - Color Imaging XXI: Displaying, Processing, Hardcopy, and Applications. San Francisco, CA, USA 14 - 18 Feb 2016 Society for Imaging Science and Technology. pp. 1-7 https://doi.org/10.2352/ISSN.2470-1173.2016.20.COLOR-325
Advancing ambient assisted living with caution
Huyck, C., Augusto, J., Gao, X. and Botia, J. 2015. Advancing ambient assisted living with caution. in: Helfert, M., Holzinger, A., Ziefle, M., Fred, A., O'Donoghue, J. and Röcker, C. (ed.) Information and Communication Technologies for Ageing Well and e-Health: First International Conference, ICT4AgeingWell 2015, Lisbon, Portugal, May 20-22, 2015. Revised Selected Papers Springer.
Evaluation of colour appearances displaying on smartphones
Gao, X., Khodamoradi, E., Guo, L., Yang, X., Tang, S., Guo, W. and Wang, Y. 2015. Evaluation of colour appearances displaying on smartphones. Yaguchi, H., Okajima, K., Ishida, T., Araki, K., Doi, M. and Manabe, Y. (ed.) AIC 2015, Color and Image, Midterm meeting of the International Colour Association (AIC). Tokyo, Japan 19 - 22 May 2015 The Color Science Association of Japan. pp. 539-544
Network coding and coding-aware scheduling for multicast in wireless networks
Cheng, M.X., Ye, Q., Cheng, X. and Erbacher, R.F. 2015. Network coding and coding-aware scheduling for multicast in wireless networks. IEEE International Conference on Communications (ICC 2015). London, UK 08 - 12 Jun 2015 IEEE. pp. 5703-5708 https://doi.org/10.1109/ICC.2015.7249231
The application of KAZE features to the classification echocardiogram videos
Li, W., Qian, Y., Loomes, M. and Gao, X. 2015. The application of KAZE features to the classification echocardiogram videos. First International Workshop Multimodal Retrieval in the Medical Domain (MRMD 2015). Vienna, Austria 29 Mar 2015 Springer. pp. 61-72 https://doi.org/10.1007/978-3-319-24471-6_6
Modelling of chromatic contrast for retrieval of wallpaper images
Gao, X., Wang, Y., Qian, Y. and Gao, A. 2015. Modelling of chromatic contrast for retrieval of wallpaper images. Color Research and Application. 40 (4), pp. 361-373. https://doi.org/10.1002/col.21897
Numeric characteristics of generalized M-set with its asymptote
Liu, S., Cheng, X., Fu, W., Zhou, Y. and Li, Q. 2014. Numeric characteristics of generalized M-set with its asymptote. Applied Mathematics and Computation. 243, pp. 767-774. https://doi.org/10.1016/j.amc.2014.06.016
Local semantic indexing for resource discovery on overlay network using mobile agents
Singh, M., Cheng, X. and Belavkin, R. 2014. Local semantic indexing for resource discovery on overlay network using mobile agents. International Journal of Computational Intelligence Systems. 7 (3), pp. 432-455. https://doi.org/10.1080/18756891.2013.856257
Feature-wise representation for both still and motion 3D medical images
Gao, X. 2014. Feature-wise representation for both still and motion 3D medical images. 2014 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). San Diego, USA 06 - 09 Apr 2014 IEEE. pp. 1-4 https://doi.org/10.1109/SSIAI.2014.6806014
Cardiac motion reconstruction using LKT algorithm from 2D and 3D echocardiography
Gao, A., Li, W., Lin, C., Loomes, M. and Gao, X. 2013. Cardiac motion reconstruction using LKT algorithm from 2D and 3D echocardiography. in: IPCV'13 - The 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition CSRES Press.
Fractal property of generalized M-set with rational number exponent
Liu, S., Cheng, X., Lan, C., Fu, W., Zhou, J., Li, Q. and Gao, G. 2013. Fractal property of generalized M-set with rational number exponent. Applied Mathematics and Computation. 220, pp. 668-675. https://doi.org/10.1016/j.amc.2013.06.096
Mechanical verification of cryptographic protocols
Cheng, X., Ma, X., Huang, S. and Cheng, M. 2010. Mechanical verification of cryptographic protocols. Network Security. https://doi.org/10.1007/978-0-387-73821-5_5
DNSsec in Isabelle – replay attack and origin authentication
Kammueller, F., Kirsal-Ever, Y. and Cheng, X. 2013. DNSsec in Isabelle – replay attack and origin authentication. SMC 2013: IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK 13 - 16 Oct 2013 IEEE. pp. 4772-4777 https://doi.org/10.1109/SMC.2013.812
The synergy of 3D SIFT and sparse codes for classification of viewpoints from echocardiogram videos
Qian, Y., Wang, L., Wang, C. and Gao, X. 2013. The synergy of 3D SIFT and sparse codes for classification of viewpoints from echocardiogram videos. Greenspan, H., Müller, H. and Syeda-Mahmood, T. (ed.) 3rd MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support. Nice, France 01 - 01 Oct 2012 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-642-36678-9_7
3D CBIR with sparse coding for image-guided neurosurgery
Qian, Y., Hui, R. and Gao, X. 2013. 3D CBIR with sparse coding for image-guided neurosurgery. Signal Processing. 93 (6), pp. 1673-1683. https://doi.org/10.1016/j.sigpro.2012.10.020
Bridging the abridged – the diffusion of Telemedicine in Europe and China
Gao, X., Loomes, M. and Comley, R. 2012. Bridging the abridged – the diffusion of Telemedicine in Europe and China. in: Rodrigues, J., Díez, I. and Abajo, B. (ed.) Telemedicine and e-health services, policies, and applications: avancements and developments USA IGI Global. pp. 451-495
The state of the art of medical imaging technology: from creation to archive and back.
Gao, X., Qian, Y. and Hui, R. 2011. The state of the art of medical imaging technology: from creation to archive and back. The Open Medical Informatics Journal. 5 (1-M8), pp. 73-85. https://doi.org/10.2174/1874431101105010073
A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA
Wang, S., Li, W., Cheng, X., Wang, Y. and Jiang, Y. 2012. A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA. Advances in Information Sciences and Service Sciences. 4 (23), pp. 181-188. https://doi.org/10.4156/AISS.vol4.issue23.23
A cooperative particle swarm optimizer with statistical variable interdependence learning
Sun, L., Yoshida, S., Cheng, X. and Liang, Y. 2012. A cooperative particle swarm optimizer with statistical variable interdependence learning. Information Sciences. 186 (1), pp. 20-39. https://doi.org/10.1016/j.ins.2011.09.033
Survey of grid resource monitoring and prediction strategies.
Hu, L., Cheng, X. and Che, X. 2010. Survey of grid resource monitoring and prediction strategies. International Journal of Intelligent Information Processing. 1 (2).
Efficient identity-based broadcast encryption without random oracles.
Hu, L., Liu, Z. and Cheng, X. 2010. Efficient identity-based broadcast encryption without random oracles. Journal of Computers. 5 (3), pp. 331-336.
Solving job shop scheduling problem using genetic algorithm with penalty function
Sun, L., Cheng, X. and Liang, Y. 2010. Solving job shop scheduling problem using genetic algorithm with penalty function. International Journal of Intelligent Information Processing. 1 (2), pp. 65-77.
Content-based petrieval of 3D medical images
Qian, Y., Gao, X., Loomes, M., Comley, R., Barn, B., Hui, R. and Tian, Z. 2011. Content-based petrieval of 3D medical images. Gemert-Pijnen, L., Ossebaard, H. and Hämäläinen, P. (ed.) eTELEMED 2011: The Third International Conference on eHealth, Telemedicine, and Social Medicine. Gosier, Guadeloupe, France 23 - 28 Feb 2011 International Academy, Research, and Industry Association (IARIA). pp. 7-12
Retrieval of 3D medical images via their texture features
Gao, X., Qian, Y., Loomes, M., Barn, B., Comley, R., Chapman, A., Rix, J., Hui, R. and Tian, Z. 2011. Retrieval of 3D medical images via their texture features. International Journal on Advances in Software. 4 (3&4), pp. 499-509.
The anatomy of teleneurosurgery in China
Gao, X. 2011. The anatomy of teleneurosurgery in China. International Journal of Telemedicine and Applications. 2011. https://doi.org/10.1155/2011/353405
Texture-based 3d image retrieval for medical applications
Gao, X., Qian, Y., Hui, R., Loomes, M., Comley, R., Barn, B., Chapman, A. and Rix, J. 2010. Texture-based 3d image retrieval for medical applications. Macedo, M. (ed.) IADIS International Conference e-Health 2010. Freiburg, Germany 29 - 31 Jul 2010 IADIS. pp. 101-108
Application of mesh morphing techniques in modelling 3D objects
Gao, X. and Hassan, M. 2010. Application of mesh morphing techniques in modelling 3D objects. Annual International Conference on Computer Games Multimedia and Allied Technology. Singapore 06 - 07 Apr 2010 Global Science and Technology Forum. https://doi.org/10.5176/978-981-08-5480-5_048
Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization
Cheng, X., Che, X. and Hu, L. 2010. Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization. International Journal of Computational Intelligence Systems. 3 (1), pp. 70-83. https://doi.org/10.2991/ijcis.2010.3.1.7
Resource discovery using mobile agents
Singh, M., Cheng, X. and Belavkin, R. 2010. Resource discovery using mobile agents. Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference. Changchun, Jilin Province 18 - 22 Aug 2010 IEEE. pp. 72 -77 https://doi.org/10.1109/FCST.2010.93
Road sign recognition by one fixation of space-variant sensor.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N. and Hong, K. 2002. Road sign recognition by one fixation of space-variant sensor. in: Gorodnich, D. and Zhang, H. (ed.) Vision Interface ’2002: proceedings Quebec Canadian Image Processing and Pattern Recognition Society.
Invariant recognition of traffic signs
Gao, X., Shaposhnikov, D., Podladchikova, L., Shevtsova, N. and Golovan, A. 2002. Invariant recognition of traffic signs.
Application of the behavioural model of vision for invariant recognition of facial and traffic sign images.
Gao, X., Shaposhnikov, D., Podladchikova, L., Golovan, A., Shevtsova, N., Gusakova, V. and Gizatdinova, Y. 2003. Application of the behavioural model of vision for invariant recognition of facial and traffic sign images. in: Gulaev, Y. and Galushkin, A. (ed.) Neurocomputers and their application. [In Russian] Moscow Radiotechnics.
Image classification based on the informative regions properties.
Gao, X., Podladchikova, L. and Shaposhnikov, D. 2003. Image classification based on the informative regions properties. in: Proceedings of PRIA-6-2002 : 6th International conference on pattern recognition and image analysis: new information technologies. MAIK Nauka/Interperiodica. pp. 439-441
Image retrieval through perceptual shape modelling.
Gao, X., Ren, M., Riley, K., Eakins, J. and Briggs, P. 2001. Image retrieval through perceptual shape modelling. London Council for Museums, Archives and Libraries.
Telemedicine in Europe.
Gao, X. 2006. Telemedicine in Europe. ChinaPacs. Beijing 14 - 16 Apr 2006
A new approach to traffic sign recognition
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K., Batty, S., Golovan, A., Gusakova, V. and Shevtsova, N. 2002. A new approach to traffic sign recognition. in: Arabnia, H. and Mun, Y. (ed.) Proceedings of the international conference on imaging science, systems, and technology: CISST'02. Athens CSREA Press.
Road sign recognition by means of the behavioural model of vision.
Gao, X., Golovan, A., Hong, K., Podladchikova, L. and Shevtsova, N. 2002. Road sign recognition by means of the behavioural model of vision. in: Proceedings of the third all-Russian conference on neuroinformatics [In Russian]. Moscow. pp. 63-69
Colour reproduction for tele-imaging systems
Gao, X. and He, P. 2006. Colour reproduction for tele-imaging systems. Computerized medical imaging and graphics. 30 (6-7), pp. 79-84.
Measurement of vessel diameters on retinal for cardiovascular studies.
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. Measurement of vessel diameters on retinal for cardiovascular studies. in: Claridge, E., Bamber, J. and Marlow, K. (ed.) Medical image understanding and analysis 2001. Medical Imaging Understanding and Analysis.
Extraction of sagittal symmetry planes from PET images.
Gao, X., Batty, S., Clark, J., Fryer, T., Blandford, A. and International Association of Science and Technology for Development. 2001. Extraction of sagittal symmetry planes from PET images. in: Hamza, M. (ed.) Visualization, imaging and image processing: proceedings of the IASTED international conference. Calgary IASTED. pp. 428-433
Towards archiving wallpaper images
Gao, X., Qian, Y., Tully, T. and Hendon, Z. 2004. Towards archiving wallpaper images. in: Hamza, M. (ed.) Proceedings of the seventh IASTED international conference on computer graphics and imaging. Anaheim Acta Press. pp. 305-309
High-precision detection of facial landmarks to estimate head motions based on vision models
Gao, X., Anishenko, S., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. High-precision detection of facial landmarks to estimate head motions based on vision models. Journal of computer sciences. 3 (7), pp. 528-532.
Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels
Gao, X., Batty, S., Clark, J. and Fryer, T. 2006. Content-based retrieval of PET images via localised anatomical texture measurements and mean activity levels. Computerized medical imaging and graphics. 30 (6-7), pp. 70-74.
Extraction of physiological information from 3D PET brain images.
Gao, X., Batty, S., Fryer, T., Clark, J., Turkheimer, F. and International Association of Science and Technology for Development. 2003. Extraction of physiological information from 3D PET brain images. in: Villanueva, J. (ed.) Visualization imaging and image processing. Acta Press. pp. 401-405
Extraction of features from 3D PET images.
Gao, X., Batty, S., Clark, J. and Fryer, T. 2002. Extraction of features from 3D PET images. in: Houston, A. and Zwiggelar, R. (ed.) Medical image understanding and analysis 2002. BMVA.
Towards archiving 3D PET brain images based on their physiological and visual content.
Gao, X., Batty, S., Clark, J., Fryer, T. and Turkheimer, F. 2002. Towards archiving 3D PET brain images based on their physiological and visual content. International conference on diagnostic imaging and analysis. Shanghai, China 18 - 20 Aug 2002
A new approach to estimation of non-isotropic scale factors for correction of MR distortion
Gao, X., Hui, R., White, A.S. and Tian, Z. 2009. A new approach to estimation of non-isotropic scale factors for correction of MR distortion. International Journal of Computer Assisted Radiology and Surgery. 4 (s1), pp. s349-s350.
Resource discovery using mobile agents
Singh, M., Cheng, X. and He, X. 2009. Resource discovery using mobile agents. in: Tao, D., Xu, D. and Li, X. (ed.) Semantic Mining Technologies for Multimedia Databases. New York, USA Information Science Reference. pp. 419-448
New e-Learning system architecture based on knowledge engineering technology
Li, Y., Chen, Z., Huang, R. and Cheng, X. 2009. New e-Learning system architecture based on knowledge engineering technology. 2009 IEEE International Conference on Systems, Man and Cybernetics. San Antonio, TX, USA 11 - 14 Oct 2009 IEEE. pp. 5140-5144 https://doi.org/10.1109/ICSMC.2009.5346013
Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals
Li, Y., Guo, H., Gao, G., Huang, R. and Cheng, X. 2009. Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals. in: Kim, J., Delen, D., Jinsoo, P., Ko, F., Rui, C., Hyung, J., Lee, W. and Kou, G. (ed.) NCM 2009: Fifth International Joint Conference on INC, IMS, and IDC; [proceedings]. IEEE. pp. 1081-1086
A fast approach to segmentation of PET brain images for extraction of features
Gao, X. and Clark, J. 2008. A fast approach to segmentation of PET brain images for extraction of features. Gao, X., Loomes, M., Comley, R., Muller, H. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_25
Prototype system for semantic retrieval of neurological PET images
Batty, S., Clark, J., Fryer, T. and Gao, X. 2008. Prototype system for semantic retrieval of neurological PET images. Gao, X., Muller, H., Loomes, M., Comley, R. and Luo, S. (ed.) International Conference on Medical Imaging and Informatics (MIMI 2007). Beijing, China 14 - 16 Aug 2007 Berlin, Heidelberg Springer. https://doi.org/10.1007/978-3-540-79490-5_23
A motion correction system for brain tomography based on biologically motivated models
Anishenko, S., Osinov, V., Shaposhnikov, D., Podladchikova, L., Comley, R., Sukholentsev, K. and Gao, X. 2008. A motion correction system for brain tomography based on biologically motivated models. 7th IEEE International Conference on Cybernetic Intelligent Systems. London, UK 09 - 10 Sep 2008 IEEE. pp. 26-30 https://doi.org/10.1109/UKRICIS.2008.4798949
Colour vision model-based approach for segmentation of traffic signs
Gao, X., Hong, K., Passmore, P., Podladchikova, L. and Shaposhnikov, D. 2008. Colour vision model-based approach for segmentation of traffic signs. EURASIP Journal on Image and Video Processing. 2008. https://doi.org/10.1155/2008/386705
Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach
Anishenko, S., Osimov, V., Shaposhnikov, D., Podladchikova, L., Comley, R. and Gao, X. 2008. Toward a robust system to monitor the head motions during PET based on facial landmarks detection: a new approach. Puuronen, S., Pechenizkiy, M., Tsymbal, A. and Lee, D. (ed.) 21st IEEE International Symposium on Computer-Based Medical Systems. Jyvaskyla, Finland 17 - 19 Jun 2008 IEEE Computer Society. pp. 50-52 https://doi.org/10.1109/CBMS.2008.19
Detection of head motions using a vision model
Gao, X., Shaposhnikov, D., Podladchikova, L., Batty, S. and Clark, J. 2007. Detection of head motions using a vision model. Bashshur, R. (ed.) 3rd IASTED International Conference on Telehealth. Montreal, QC, Canada 31 May - 01 Jun 2007 Anaheim, CA Acta Press. pp. 167-171
The state of art of medical displays.
Gao, X. 2006. The state of art of medical displays. EuroPacs 2006. Trondheim, Norway 14 - 17 Jun 2006
Recognition of traffic signs based on their colour and shape features extracted using human vision models
Gao, X., Podladchikova, L., Shaposhnikov, D., Hong, K. and Shevtsova, N. 2006. Recognition of traffic signs based on their colour and shape features extracted using human vision models. Journal of Visual Communication and Image Representation. 17 (4), pp. 675-685. https://doi.org/10.1016/j.jvcir.2005.10.003
Formal verification of the merchant registration phase of the SET protocol.
Cheng, X. and Ma, X. 2005. Formal verification of the merchant registration phase of the SET protocol. International Journal of Automation and Computing. 2 (2), pp. 155-162. https://doi.org/10.1007/s11633-005-0155-5
Programming style based program partition
Li, Y., Yang, H., Cheng, X. and Zhu, X. 2005. Programming style based program partition. International Journal of Software Engineering and Knowledge Engineering. 15 (6), pp. 1027-1061. https://doi.org/10.1142/S0218194005002610
An improved model-based method to test circuit faults
Cheng, X., Ouyang, D., Yunfei, J. and Zhang, C. 2005. An improved model-based method to test circuit faults. Theoretical Computer Science. 341 (1-3), pp. 150-161. https://doi.org/10.1016/j.tcs.2005.04.004
Colour management in telemedicine
Gao, X. 2004. Colour management in telemedicine. Hamza, M. (ed.) 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 Anaheim, CA Acta Press. pp. 361-364
Application of vision models to traffic sign recognition
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2004. Application of vision models to traffic sign recognition. Kaynak, O., Alpaydin, E., Oja, E. and Xu, L. (ed.) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. Istanbul, Turkey 26 - 29 Sep 2003 Berlin, Heidelberg Springer. https://doi.org/10.1007/3-540-44989-2_131
Topology control of ad hoc wireless networks for energy efficiency
Cheng, M., Cardei, M., Sun, J., Cheng, X., Wang, L., Xu, Y. and Du, D. 2004. Topology control of ad hoc wireless networks for energy efficiency. IEEE Transactions on Computers. 53 (12), pp. 1629-1635. https://doi.org/10.1109/TC.2004.121
Towards content-based retrieval for wallpaper images
Qian, Y., Tully, C., Hendon, Z. and Gao, X. 2003. Towards content-based retrieval for wallpaper images. 7th IASTED International Conference on Computer Graphics and Imaging. Kauai, Hawaii, United States 16 - 18 Aug 2004 pp. 305-309
Classification of images on the basis of the properties of informative regions
Gao, X., Shaposhnikov, D. and Podladchikova, L. 2003. Classification of images on the basis of the properties of informative regions. Pattern Recognition and Image Analysis. 13 (2), pp. 349-352.
Vision models based identification of traffic signs
Gao, X., Podladchikova, L., Shaposhnikov, D., Shevtsova, N., Hong, K., Batty, S., Golovan, A. and Gusakova, V. 2002. Vision models based identification of traffic signs. 1st European Conference on Colour Graphics, Imaging, and Vision. University of Poitiers, France 02 - 05 Apr 2002 Society for Imaging Science and Technology.
Content based retrieval of lesioned brain images
Batty, S., Blandford, A., Clark, J., Fryer, T. and Gao, X. 2002. Content based retrieval of lesioned brain images. Siegel, E. and Huang, H. (ed.) SPIE Medical Imaging 2002. San Diego, California, United States 23 - 28 Feb 2002 Bellingham Society of Photo-optical Instrumentation Engineers (SPIE). https://doi.org/10.1117/12.466997
A method of vessel tracking for vessel diameter measurement on retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2001. A method of vessel tracking for vessel diameter measurement on retinal images. 2001 International Conference on Image Processing. Thessaloniki, Greece 07 - 10 Oct 2001 IEEE.
Computer algorithms for the automated measurement of retinal arteriolar diameters
Chapman, N., Witt, N., Gao, X., Bharath, A., Stanton, A., Thom, S. and Hughes, A. 2001. Computer algorithms for the automated measurement of retinal arteriolar diameters. British Journal of Ophthalmology. 85 (1), pp. 74-79. https://doi.org/10.1136/bjo.85.1.74
Quantification and characterization of arteries in retinal images
Gao, X., Bharath, A., Stanton, A., Hughes, A., Chapman, N. and Thom, S. 2000. Quantification and characterization of arteries in retinal images. Computer Methods and Programs in Biomedicine. 63 (2), pp. 133-146. https://doi.org/10.1016/S0169-2607(00)00082-1