Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures
Conference Proceeding
Zheng, C., Zhen, C., Xie, H., & Yang, S. (2022)
Towards Secure Multi-Agent Deep Reinforcement Learning: Adversarial Attacks and Countermeasures. In 2022 IEEE Conference on Dependable and Secure Computing (DSC). https://doi.org/10.1109/dsc54232.2022.9888828
Reinforcement Learning (RL) is one of the most popular methods for solving complex sequential decision-making problems. Deep RL needs careful sensing of the environment, selec...
Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models
Journal Article
Ji, Y., Yang, S., Zhou, K., Lu, J., Wang, R., Rocliffe, H. R., …Huang, Z. (2022)
Semi-supervised Representative Learning for Measuring Epidermal Thickness in Human Subjects in Optical Coherence Tomography by Leveraging Datasets from Rodent Models. Journal of Biomedical Optics, 27(8), Article 085002. https://doi.org/10.1117/1.JBO.27.8.085002
Aim: Morphological changes in the epidermis layer are critical for the diagnosis and assessment of various skin diseases. Due to its non-invasiveness, optical coherence tomogr...
Co-optimization method to improve lateral resolution in photoacoustic computed tomography
Journal Article
Zhang, Y., Yang, S., Xia, Z., Hou, R., Xu, B., Hou, L., …Xiong, J. (2022)
Co-optimization method to improve lateral resolution in photoacoustic computed tomography. Biomedical Optics Express, 13(9), 4621-4636. https://doi.org/10.1364/BOE.469744
In biomedical imaging, photoacoustic computed tomography (PACT) has recently gained increased interest as this imaging technique has good optical contrast and depth of acousti...
Thermography for Disease Detection in Livestock: A Scoping Review
Journal Article
McManus, R., Boden, L., Weir, W., Viora, L., Barker, R., Kim, Y., …Yang, S. (2022)
Thermography for Disease Detection in Livestock: A Scoping Review. Frontiers in Veterinary Science, 9, Article 965622. https://doi.org/10.3389/fvets.2022.965622
Infra-red thermography (IRT) offers potential opportunities as a tool for disease detection in livestock. Despite considerable research in this area, there are no common stand...
Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation
Journal Article
Thomson, H., Yang, S., & Cochran, S. (2022)
Machine Learning Enabled Quantitative Ultrasound Techniques for Tissue Differentiation. Journal of Medical Ultrasonics, 49, 517-528. https://doi.org/10.1007/s10396-022-01230-6
Quantitative ultrasound (QUS) infers properties about tissue microstructure from backscattered via radio-frequency ultrasound data. This paper describes how to implement the m...
Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography
Journal Article
Ji, Y., Yang, S., Zhou, K., Rocliffe, H. R., Pellicoro, A., Cash, J. L., …Huang, Z. (2022)
Deep Learning Approach for Automated Thickness Measurement of Epithelial Tissue and Scab using Optical Coherence Tomography. Journal of Biomedical Optics, 27(1), https://doi.org/10.1117/1.JBO.27.1.015002
Significance: In order to elucidate therapeutic treatment to accelerate wound healing, it is crucial to understand the process underlying skin wound healing, especially re-epi...
Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning
Journal Article
Parra-Ullauri, J. M., Garcoa-Dominguez, A., Bencomo, N., Zheng, C., Zhen, C., Boubeta-Puig, J., …Yang, S. (2022)
Event-driven Temporal Models for Explanations - ETeMoX: Explaining Reinforcement Learning. Software and Systems Modeling, 21, 1091-1113. https://doi.org/10.1007/s10270-021-00952-4
Modern software systems are increasingly expected to show higher degrees of autonomy and self-management to cope with uncertain and diverse situations. As a consequence, a...
Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems
Journal Article
Zheng, C., Yang, S., Parra-Ullauri, J., Garcia-Dominguez, A., & Bencomo, N. (2022)
Reward-Reinforced Generative Adversarial Networks for Multi-agent Systems. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(3), 479 - 488. https://doi.org/10.1109/TETCI.2021.3082204
Multi-agent systems deliver highly resilient and adaptable solutions for common problems in telecommunications, aerospace, and industrial robotics. However, achieving an optim...
Hierarchical Radar Data Analysis for Activity and Personnel Recognition
Journal Article
Li, X., Li, Z., Fioranelli, F., Yang, S., Romain, O., & Kernec, J. L. (2020)
Hierarchical Radar Data Analysis for Activity and Personnel Recognition. Remote Sensing, 12(14), https://doi.org/10.3390/rs12142237
Radar-based classification of human activities and gait have attracted significant attention with a large number of approaches proposed in terms of features and classification...
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy
Journal Article
Ali, S., Zhou, F., Braden, B., Bailey, A., Yang, S., Cheng, G., …Rittscher, J. (2020)
An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy. Scientific Reports, 10(1), https://doi.org/10.1038/s41598-020-59413-5
We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a ste...