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Outputs (4)

Activity Classification Using Raw Range and I & Q Radar Data with Long Short Term Memory Layers (2018)
Presentation / Conference Contribution
Loukas, C., Fioranelli, F., Le Kernec, J., & Yang, S. (2018, August). Activity Classification Using Raw Range and I & Q Radar Data with Long Short Term Memory Layers. Presented at 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), Athens, Greece

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. Although tested only on simple classification problems, this is an innovative app... Read More about Activity Classification Using Raw Range and I & Q Radar Data with Long Short Term Memory Layers.

A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection (2018)
Presentation / Conference Contribution
Yu, Z., Yang, S., Zhou, K., & Aggoun, A. (2018, September). A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection. Presented at UK Workshop on Computational Intelligence, Nottingham

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 adenocarcinoma and colorectal cancer. Rich statistical features are used to tr... Read More about A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection.

A single chip system for sensor data fusion based on a Drift-diffusion model (2018)
Presentation / Conference Contribution
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 hardware and software co-design platform for a heterogeneous data fusion sol... Read More about A single chip system for sensor data fusion based on a Drift-diffusion model.

Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device (2018)
Presentation / Conference Contribution
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/software co-design. An urgent need of creating a scalable hardware/software co-des... Read More about Towards a scalable hardware/software co-design platform for real-time pedestrian tracking based on a ZYNQ-7000 device.