研究领域：

[1]视觉认知与计算，脑认知科学，视觉注意，生物视觉计算

[2]图像/视频处理，计算机视觉，深度学习，模式识别

[3]智能交通驾驶

[Google Scholar]

[ResearchGate]

已发表论文：

[1] Tao Deng, Lianfang Jiang, Yi Shi, Jiang Wu, Zhangbi Wu, Shun Yan, Xianshi Zhang*, and Hongmei Yan*. Driving Visual Saliency Prediction of Dynamic Night Scenes via a Spatio-Temporal Dual-Encoder Network. IEEE Transactions on Intelligent Transportation Systems (TITS), 2024, 25 (3), 2413-2423.

[2] Yi Huang and Tao Deng*. Multi-level spatial-temporal and attentional information deep fusion network for retinal vessel segmentation. Physics in Medicine & Biology. 2023, 68 (19), 195026.

[3] Pengcheng Du#, Tao Deng#, Fei Yan*. What Causes a Driver's Attention Shift? A Driver's Attention-Guided Driving Event Recognition Model. International Joint Conference on Neural Networks (IJCNN), 2023.

[4] Han Tian, Tao Deng*, and Hongmei Yan. Driving as well as on a Sunny Day? Predicting Driver's Fixation in Rainy Weather Conditions via a Dual-branch Visual Model. IEEE/CAA Journal of Automatica Sinica, 2022, 9(7): 1335-1338.

[5] Long Qin, Yi Shi, Yahui He, Junrui Zhang, Xianshi Zhang, Yongjie Li, Tao Deng* and Hongmei Yan*. ID-YOLO: Real-Time Salient Object Detection Based on the Driver's Fixation Region.  IEEE Transactions on Intelligent Transportation Systems (TITS), 2022, 23(9): 15898-15908.

[6]  Jiyong Zhang,  Tao Deng* , Fei Yan, Wenbo Liu. Lane Detection Model Based on Spatio-Temporal Network with Double Convolutional Gated Recurrent Units.  IEEE Transactions on Intelligent Transportation Systems (TITS ), 2022, 23(7): 6666-6678.

 [7] Junfeng Zhang, Fei Yan, Tao Feng, Tao Deng, Yue Zhao. Fastest containment control of discrete-time multi-agent systems using static linear feedback protocol. Information Sciences, 2022, 614: 362-373.

[8]  Jiyong Zhang, Tao Deng* and Fei Yan. TARConvGRU: A Cross-dimension Spatiotemporal Model for Lane Detection. International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-7, doi: 10.1109/IJCNN55064.2022.9892594.

[9]  Lin Sun, Fei Yan, Tao Deng*, Chenran Jiang, Jun Li. A Lightweight Network with Lane Feature Enhancement for Multilane Drivable Area Detection. 14th International Conference on Wireless Communications and Signal Processing (WCSP), 2022.

[10]  Yi Huang, Tao Deng*. STSANet: Retinal Vessel Segmentation via Spatial-Temporal and Self-Attention Encoding. 14th International Conference on Wireless Communications and Signal Processing (WCSP), 2022.

[11]  Chenran Jiang, Fei Yan, Tao Deng*, Lin Sun, Jun Li. TSANet: Two-subnet Attention Network for Single Image Dehazing. 14th International Conference on Wireless Communications and Signal Processing (WCSP), 2022.

[12]  Shihui Ji, Tao Deng*, Fei Yan and Pengcheng Du. A Driving Position-Sensitive Neural Network for Driver Fixation Prediction. 2022 41st Chinese Control Conference (CCC), 2022, pp. 6660-6665.

[13]  Tao Deng*, Fei Yan, Hongmei Yan. Driving Video Fixation Prediction Model via Spatio-Temporal Networks and Attention Gates. IEEE International Conference on Multimedia and Expo (ICME), 2021, pp. 1-6, doi: 10.1109/ICME51207.2021.9428151.

[14]  Wenbo Liu, Fei Yan, Jiyong Zhang, Tao Deng*. A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information. Sensors, 21(3), 708, 2021. https://doi.org/10.3390/s21030708

[15]  Tao Deng, Hongmei Yan, Long Qin, Thuyen Ngo, B.S. Manjunath. How Do Drivers Allocate Their Potential Attention?Driving Fixation Prediction via Convolutional Neural Networks. IEEE Transactions on Intelligent Transportation Systems (TITS),21(5): 2146-2154, 2020.

[16]  Tao Deng, Hongmei Yan, Yongjie Li. Learning to Boost Bottom-up Fixation Prediction in Driving Environments via Random Forest. IEEE Transactions on Intelligent Transportation Systems (TITS), 19(9): 3059-3067, 2018.

[17]  Tao Deng, Kaifu Yang, Yongjie Li, Hongmei Yan. Where does the driver look? Top-down-based saliency detection in a traffic driving environment. IEEE Transactions on Intelligent Transportation Systems (TITS), 17(7): 2051-2062, 2016.

[18]  Tao Deng, Andong Chen, Min Gao, Hongmei Yan. Top-down based saliency model in traffic driving environment. IEEE International Conference on Intelligent Transportation Systems (ITSC), PP. 75-80, 2014.

[19]  邓涛, 罗恩晴, 张艳山, 颜红梅. 基于选择性注意的交通环境显著性及眼动特征研究. 电子科技大学学报, 43(4): 624-628, 2014.

[20]  Wenbo Liu, Fei Yan, Kuan Tang, Jiyong Zhang, Tao Deng. Lane detection in complex scenes based on end-to-end neural network. Chinese Automation Congress (CAC), Shanghai, China, 2020, pp. 4300-4305, doi: 10.1109/CAC51589.2020.9327660.

[21]  Xufang Chen, Tao Deng, Hongmei Yan. Non-Linearity of Visual Sensitivity and Pursuit Velocity during Smooth Pursuit Eye Movements. Journal of Electronic Science and Technology, 12(4): 394-399, 2014.

[22]  邓涛, 颜红梅. 动态驾驶场景中驾驶员的眼动特性研究. 心理科学进展, 24(Suppl.): 54, 2016.

[23]  Tao Deng, Enqing Luo, Hongmei Yan. Computational modeling of visual selective attention in road traffic environment. Psych Journal, 2: 15-16, 2013.

主持科研项目：

国家自然科学基金青年科学基金项目，复杂驾驶场景下基于时空注意的驾驶安全预测研究，2022.01-2024.12

四川省自然科学基金青年基金，面向复杂天气条件的驾驶场景视觉注意计算模型，2023.01-2024.12

中国博士后科学基金特别资助（站前），面向复杂驾驶场景的驾驶安全预警研究，2021.07-2023.06

中国博士后科学基金面上资助，基于驾驶任务引导的时空注视信息检测模型研究，2021.11-2023.10

西南交通大学新型交叉学科培育基金，基于视觉认知机理的驾驶环境感知计算模型研究，2022.11-2024.10

四川省科技计划项目-科技创新创业项目，面向复杂驾驶场景的视觉感知计算模型，2020.01-2021.12

神经信息教育部重点实验室开放课题，复杂驾驶场景中的视觉注意理论及计算模型研究，2020.08-2021.12

中央高校基本科研业务费，基于视觉注意的计算模型在复杂驾驶场景中的应用，2019.01-2021.12