教育工作经历

2023.07-至今 东莞理工学院， 国际微电子学院， 讲师

2020.09-2023.07 澳门科技大学，计算机技术及其应用，博士

学术成果介绍

一．项目

[1] 超声内镜对上消化道黏膜下肿物病变的多模态诊断关键技术研究，澳门科学技术发展基金, 2023.1-2025.12，参与。

[2] 基于计算机深度学习的上消化道早癌诊疗辅助程序的研发与优化， 澳门科学技术发展基金-国家自然科学基金联合项目, 2019.1-2022.1，参与。

二．论文

[1] S. Tang, X. Yu, C.F. Cheang, Y. Liang, P. Zhao, H.H. Yu, and I.C. Choi, “Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images,” Computers in Biology and Medicine, vol. 157, pp. 106723, 2023.

[2] S. Tang, C.F. Cheang, X. Yu, Y. Liang, Q. Feng, and Z. Chen, “TransCS-Net: a hybrid transformer-based privacy-protecting network using compressed sensing for medical image segmentation,” Biomedical Signal Processing and Control, vol. 86, pp. 105131, 2023.

[3] S. Tang, and Z. Deng, “CS-based multi-task learning network for arrhythmia reconstruction and classification using ECG signals,” Physiological Measurement, vol. 44, no. 7, pp. 075001, 2023.

[4] S. Tang, X. Yu, C.F. Cheang, X. Ji, H.H. Yu, and I.C. Choi, “CLELNet: a continual learning network for esophageal lesion analysis on endoscopic images,” Computer Methods and Programs in Biomedicine, vol. 231, pp. 107399, 2023.

[5] P. Zhao, H. Zheng, S. Tang, Z. Chen, and Y. Liang, “DAMNet: a dual adjacent indexing and multi-deraining network for real-time image deraining,” Fractal and Fractional, vol, 7, no. 1, pp. 24, 2022.

[6] S. Tang, X. Yu, C.F. Cheang, Z. Hu, T. Fang, I.C. Choi, and H.H. Yu, “Diagnosis of esophageal lesions by multi-classification and segmentation using an improved multi-task deep learning model”, Sensors, vol. 22, no. 4, pp. 1492, 2022.

[7] X. Yu, S. Tang, C.F. Cheang, H.H. Yu, and I.C. Choi, “Multi-task model for esophageal lesion analysis using endoscopic images: classification with image retrieval and segmentation with attention”, Sensors, vol. 22, no. 1, pp. 283, 2021.

三．专利

[1] 唐穗谷,许银亮.一种基于实时压缩感知的多地区电力控制方法. 201710578516.8。

[2] 唐穗谷,许银亮,但唐也.一种基于压缩传感的智能电表数据的实时重构方法. 201810520192.7。