巨乳美女

助理教授&讲师

  • 唐穗谷讲师
    个人主页://jurumn.com/info/1125/4134.htm
    专业方向:智能医疗,深度学习及人工智能
        
​教育工作经历

2023.07-至今 巨乳美女 , 巨乳美女 , 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] 基于自然语言大模型的儿童上肢骨折智能诊断的算法及应用研究,广东区域联合基金-青年基金项目,2025.1-2027.12,主持。

[2] 面向内窥镜肠胃道病变智能诊断的多模态关键技术研究,广西高校智能软件重点实验室,2025.1-2026.12,主持。

[3] 高效抑菌防漏多层可降解芯体的研究与应用,企业横向课题,2023.5-2025.12,主持。

[4] 面向自动驾驶安全的交通灯检测和轨迹规划风险决策的关键技术研究,澳门科学技术发展基金, 2024.1-2026.12,核心成员。

[5] 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核心成员

[6] 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核心成员

.论文(*代表通讯作者)

[1] X. Chen, Z. Li, S. Tang*, J. Li, H. Liu, J. Nong, “EDSDF: An Efficient Deep Supervised Distillation Framework for Medical Image Segmentation, Neurocomputing, 2025, Accept.

[2] X. Ji, Z. Sun, H. Lv, X. Yu, S. Tang*, D. Zhang, Y. Liang*, “Spatio-temporal multivariable time vario-zoom network for water level forecasting based on high-resolution hydrological dataset,Journal of Hydrology. Vol. 634, pp. 131016, 2024.

[3] Z. Li, K. Liu, S. Tang*, J. Li, C.F. Cheang, “FDDA-Unet: A Frequency-Domain-based Lightweight Network Used for Medical Image Segmentation,2024 IEEE 5th International Conference on Computers and Artificial Intelligence Technology. 2024. (EI)

[4] J. Li, C.F. Cheang*, S. Liu, S. Tang, T. Li, Q. Cheng, “Dynamic-TLD: a traffic light detector based on dynamic strategies,IEEE Sensors Journal, vol24, no.5, pp. 6677-6686, 2024.

[5] 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.

[6] 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.

[7] 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.

[8] 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.

[9] 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.

[10] 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.

[11] 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.

[12] S. Tang, Y. Xu*, and X. Tang, “Real-time reconstruction of multi-area power system signals based on compressed sensing,” 2017 China International Electrical and Energy Conference (CIEEC), pp.377-382, 2017. (EI).

[13] S. Tang, Y. Xu*, “Distributed control of multi-zone commercial building for demand response,” 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), pp.1-5, 2017. (EI).

.专利

1)授权:

[1] 郑泽峰,唐穗谷,梁延研,于晓渊,余汉濠,徐义祥. 基于多任务辅助的上消化道病变区域确定方法及装置. 202110930193.0.

[2] 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.

[3] 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.

2)申请:

[4] 唐穗谷,刘华珠,林俊辉,赵晓芳,陈雪芳,郑泽峰. 一种基于 transformer 的肠胃道内窥镜图像分类和分割方法. 202311737973.9.

[5] 唐穗谷,刘华珠,陈雪芳,李伟恒,温思业,陈剑先,冯建铭. 一种基于医学属性驱动的少样本消化道疾病诊断方法及装置. 202510490788.7.

[6] 李志宁,唐穗谷,陈雪芳,刘华珠,欧立宏,杨卓翰. 一种应用于医疗图像分割的高效深度监督蒸馏方法及装置. 202510490677.6.

[7] 刘华珠,李乐,唐穗谷,林盛鑫,郭素峡. 一种基于多模态融合的心血管疾病预测系统. 202411589595.9.

四.指导学生科研项目

[1] 大学生创新创业训练计划. 基于STM32与深度学习的智能垃圾分类系统设计与应用 (省级). 2025.

[2] 大学生创新创业训练计划. 基于深度学习的多模态内窥镜图像智能诊断研究 (校级). 2024.

[3] 杨振宁创新班学生导师制科研项. 基于 Transformer 的上消化道粘膜肿物病变智能诊断研究 . 2024.


分享到: