Building a Reusable and Extensible Automatic Compiler Infrastructure for reconfigurable devices
Conference Proceeding
Zang, Z., Dolinsky, U., Ghiglio, P., Cherubin, S., Goli, M., & Yang, S. (2023)
Building a Reusable and Extensible Automatic Compiler Infrastructure for reconfigurable devices. In 2023 33rd International Conference on Field-Programmable Logic and Applications (FPL) (351-352). https://doi.org/10.1109/FPL60245.2023.00062
Multi-Level Intermediate Representation (MLIR) is gaining increasing attention in reconfigurable hardware communities due to its capability to represent various abstract level...
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...
A Machine Learning Based Quantitative Data Analysis for Screening Skin Diseases Based on Optical Coherence Tomography Angiography (OCTA)
Conference Proceeding
Ji, Y., Yang, S., Zhou, K., Li, C., & Huang, Z. (2021)
A Machine Learning Based Quantitative Data Analysis for Screening Skin Diseases Based on Optical Coherence Tomography Angiography (OCTA). In 2021 IEEE International Ultrasonics Symposium (IUS)https://doi.org/10.1109/IUS52206.2021.9593642
Lack of accurate and standard quantitative evaluations limit the progress of applying the OCTA technique into skin clinical trials. More systematic research is required to inv...
Effect of Freezing and Fixation on Quantitative Ultrasound Parameters in Phantoms of Brain and Brain Tumour
Conference Proceeding
Thomson, H., Yang, S., Cochran, S., Stritch, T., & Baldwin, M. (2020)
Effect of Freezing and Fixation on Quantitative Ultrasound Parameters in Phantoms of Brain and Brain Tumour. In 2020 IEEE International Ultrasonics Symposium (IUS). https://doi.org/10.1109/ius46767.2020.9251780
Quantitative ulltrasound (QUS) analyzes unprocessed radio frequency data from an ultrasound transducer or array and infers properties about tissue microstructure. Whilst it ha...
Deep Compressed Sensing for Characterizing Inflammation Severity with Microultrasound
Conference Proceeding
Yang, S., Lemke, C., Cox, B. F., Newton, I. P., Cochran, S., & Nathke, I. (2020)
Deep Compressed Sensing for Characterizing Inflammation Severity with Microultrasound. In 2020 IEEE International Ultrasonics Symposium (IUS). https://doi.org/10.1109/ius46767.2020.9251280
With histological information on inflammation status as the ground truth, deep learning methods can be used as a classifier to distinguish different stages of bowel inflammati...
Activity Classification Using Raw Range and I & Q Radar Data with Long Short Term Memory Layers
Conference Proceeding
Loukas, C., Fioranelli, F., Le Kernec, J., & Yang, S. (2018)
Activity Classification Using Raw Range and I & Q Radar Data with Long Short Term Memory Layers. In 2018 IEEE 16th Intl Conf on Dependable, Autonomic and Secure Computing, 16th Intl Conf on Pervasive Intelligence and Computing, 4th Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress(DASC/PiCom/DataCom/CyberSciTech). https://doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00088
This paper presents the first initial results of using radar raw I & Q data and range profiles combined with Long Short Term Memory layers to classify human activities. Althou...
A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection
Conference Proceeding
Yu, Z., Yang, S., Zhou, K., & Aggoun, A. (2019)
A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection. In Advances in Computational Intelligence Systems: Contributions Presented at the 18th UK Workshop on Computational Intelligence. , (169-178). https://doi.org/10.1007/978-3-319-97982-3_14
In this paper, we aim to develop a low-computational system for real-time image processing and analysis in endoscopy images for the early detection of the human esophageal ade...
A single chip system for sensor data fusion based on a Drift-diffusion model
Conference Proceeding
Yang, S., Wong-Lin, K., Rano, I., & Lindsay, A. (2018)
A single chip system for sensor data fusion based on a Drift-diffusion model. In 2017 Intelligent Systems Conference (IntelliSys). https://doi.org/10.1109/intellisys.2017.8324291
Current multisensory system face data communication overhead in integrating disparate sensor data to build a coherent and accurate global phenomenon. We present here a novel h...
Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device
Conference Proceeding
Yu, W., Yang, S., Sillitoe, I., & Buckley, K. (2018)
Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device. https://doi.org/10.1109/icce-asia.2017.8307853
Currently, most designers face a daunting task to research different design flows and learn the intricacies of specific software from various manufacturers in hardware/softwar...
Interactive Reading Using Low Cost Brain Computer Interfaces
Conference Proceeding
Loizides, F., Naughton, L., Wilson, P., Loizou, M., Yang, S., Hartley, T., …Zaphiris, P. (2017)
Interactive Reading Using Low Cost Brain Computer Interfaces. In Human-Computer Interaction – INTERACT 2017 Proceedings, Part IV. , (450-454). https://doi.org/10.1007/978-3-319-68059-0_49
This work shows the feasibility for document reader user applications using a consumer grade non-invasive BCI headset. Although Brain Computer Interface (BCI) type devices are...