|
杨彪 工学博士、副教授 |
常州大学 王诤微电子学院 集成电路产业学院
江苏常州 213164 | |
|
教育背景: |
2005.09-2009.07 南京工业大学自动化学院 自动化专业 工学学士 2009.09-2014.11 东南大学仪器科学与工程学院 仪器科学与技术 工学博士 |
工作履历: |
2020.11- 河海大学人工智能学院，博士后 2020.12- 常州大学王诤微电子学院，副教授 2014.11-2020.11 常州大学信息科学与工程学院，讲师 2018.08-2019.09 加州大学伯克利分校，访问学者 |
主授课程: |
机器视觉及应用 Python程序设计 机器学习 |
研究领域: |
人工智能 模式识别 自动驾驶 |
奖励与荣誉: |
1. 2024年发明创业奖创新奖一等奖 2. 2015年校青年教师课堂教学技艺大赛二等奖 3. 2020年常州大学高等教育教学成果奖二等奖 4. 2023年中国国际大学生创新大赛国赛银奖指导老师 5. 2023年第十八届中国研究生电子设计竞赛优秀指导老师 |
学术成果: |
发表论文： |
[1] Visually multimodal depression assessment based on key questions with weighted multi-task learning[J]. Signal Processing: Image Communication, 2025, 135: 117279. [2] A CVAE Combined With Diffusion Mechanism to Pedestrian Trajectory Prediction[J]. IEEE Robotics and Automation Letters, 2025. [3] Interpretable Multi-Task Prediction Neural Network for Autonomous Vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2025. [4] Asymmetric multimodal guidance fusion network for realtime visible and thermal semantic segmentation[J]. Engineering Applications of Artificial Intelligence, 2025, 142: 109881. [5] Hybrid Attention-based Multi-task Vehicle Motion Prediction Using Non-Autoregressive Transformer and Mixture of Experts[J]. IEEE Transactions on Intelligent Vehicles, 2024. [6] Probabilistic trajectory prediction of vulnerable road user using multimodal inputs[J]. IEEE Transactions on Intelligent Transportation Systems, 2024. [7] Dynamic subclass-balancing contrastive learning for long-tail pedestrian trajectory prediction with progressive refinement[J]. IEEE Transactions on Automation Science and Engineering, 2024. [8] Real-time pedestrian crossing anticipation based on an action–interaction dual-branch network[J]. IEEE Transactions on Intelligent Transportation Systems, 2024. [9] UDA-KB: Unsupervised domain adaptation RGB-Thermal semantic segmentation via knowledge bridge[C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Singapore: Springer Nature Singapore, 2024: 61-74. [10] Explainable pedestrian crossing intention prediction based on multi-task mutual guidance network[J]. IEEE Transactions on Intelligent Vehicles, 2024. [11] MMPF: multimodal purification fusion for automatic depression detection[J]. IEEE Transactions on Computational Social Systems, 2024, 11(6): 7421-7434. [12] Unlocking human-like facial expressions in humanoid robots: A novel approach for action unit driven facial expression disentangled synthesis[J]. IEEE Transactions on Robotics, 2024, 40: 3850-3865. [13] Meta-IRLSOT++: A meta-inverse reinforcement learning method for fast adaptation of trajectory prediction networks[J]. Expert Systems with Applications, 2024, 240: 122499. [14] A federated pedestrian trajectory prediction model with data privacy protection[J]. Complex & Intelligent Systems, 2024, 10(2): 1787-1799. [15] Fast adaptation trajectory prediction method based on online multisource transfer learning[J]. IEEE Transactions on Automation Science and Engineering, 2024. [16] Faster pedestrian crossing intention prediction based on efficient fusion of diverse intention influencing factors[J]. IEEE Transactions on Transportation Electrification, 2024, 10(4): 9071-9087. [17] FRPNet: An improved Faster-ResNet with PASPP for real-time semantic segmentation in the unstructured field scene[J]. Computers and Electronics in Agriculture, 2024, 217: 108623. [18] TPPO: a novel trajectory predictor with pseudo oracle[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024, 54(5): 2846-2859. [19] A multi-task learning network with a collision-aware graph transformer for traffic-agents trajectory prediction[J]. IEEE Transactions on Intelligent Transportation Systems, 2024, 25(7): 6677-6690. [20] DPCIAN: A novel dual-channel pedestrian crossing intention anticipation network[J]. IEEE Transactions on Intelligent Transportation Systems, 2023, 25(6): 6023-6034. [21] Uncertainty-aware label contrastive distribution learning for automatic depression detection[J]. IEEE Transactions on Computational Social Systems, 2023, 11(2): 2979-2989. [22] Diverse local facial behaviors learning from enhanced expression flow for microexpression recognition[J]. Knowledge-Based Systems, 2023, 275: 110729. [23] Pedestrians crossing intention anticipation based on dual‐channel action recognition and hierarchical environmental context[J]. IET Intelligent Transport Systems, 2023, 17(2): 255-269. [24] Multi-granularity scenarios understanding network for trajectory prediction[J]. Complex & Intelligent Systems, 2023, 9(1): 851-864. [25] Continual learning-based trajectory prediction with memory augmented networks[J]. Knowledge-Based Systems, 2022, 258: 110022. [26] Stability analysis of delayed-feedback control effect in the continuum traffic flow of autonomous vehicles without V2I communication[J]. Physica A: Statistical Mechanics and Its Applications, 2022, 605: 127975. [27] TrajGAT: A map-embedded graph attention network for real-time vehicle trajectory imputation of roadside perception[J]. Transportation research part C: emerging technologies, 2022, 142: 103787. [28] IRLSOT: Inverse reinforcement learning for scene‐oriented trajectory prediction[J]. IET Intelligent Transport Systems, 2022, 16(6): 769-781. [29] Facial expression recognition through cross-modality attention fusion[J]. IEEE Transactions on Cognitive and Developmental Systems, 2022, 15(1): 175-185. [30] A novel graph-based trajectory predictor with pseudo-oracle[J]. IEEE transactions on neural networks and learning systems, 2021, 33(12): 7064-7078. [31] Crossing or not? Context-based recognition of pedestrian crossing intention in the urban environment[J]. IEEE transactions on intelligent transportation systems, 2021, 23(6): 5338-5349. [32] An adversarial learned trajectory predictor with knowledge-rich latent variables[C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Cham: Springer International Publishing, 2020: 42-53. [33] Counting crowds using a scale-distribution-aware network and adaptive human-shaped kernel[J]. Neurocomputing, 2020, 390: 207-216. [34] Vision-based in situ monitoring of plankton size spectra via a convolutional neural network[J]. IEEE Journal of Oceanic Engineering, 2019, 45(2): 511-520. [35] Anomalous behaviors detection in moving crowds based on a weighted convolutional autoencoder-long short-term memory network[J]. IEEE Transactions on Cognitive and Developmental Systems, 2018, 11(4): 473-482. [36] Counting challenging crowds robustly using a multi-column multi-task convolutional neural network[J]. Signal Processing: Image Communication, 2018, 64: 118-129. |
专利成果： |
[1] 一种基于深度学习的晶圆瑕疵检测方法,ZL202211028776.5,授权； [2] 一种基于注视检测和交通场景识别的行人穿越马路意图识别方法,ZL202011276599.3,授权； [3] 一种基于图注意力自编码模型的的路侧端行人轨迹预测算法,ZL202011229257.6,授权； [4] 一种基于注意力机制融合的多通道卷积神经网络人脸表情识别方法,ZL202011276595.5,授权； [5] 一种基于穿越动作和交通场景上下文因素的行人穿越马路意图识别方法,ZL202011276593.6,授权； [6] 面向面部表情识别的双通道卷积神经网络,ZL201810599295.7,授权； [7] 加权卷积自编码长短期记忆网络人群异常检测方法,ZL201810385430.8,授权； [8] 一种对静止图像进行人群计数的方法,ZL201711179075.0,授权； |
研究项目: |
2020.05-2023.04，中国博士后科学基金面上项目，编号：2021M701042，主持 2020.05-2023.04，江苏省博士后科学基金面上项目，主持 2022.07-2025.06，江苏省科技厅面上项目，编号：BK20221380，主持 2023.01-2025.01，常州市社会发展项目，编号：CE20235037，主持 2020.05-2022.05，常州市应用基础研究计划，编号：CJ20200083，主持 2017.04-2019.03，江苏省教育厅面上项目，编号：18KJB520003，主持 2015.07-2018.06，江苏省科技厅青年项目，编号：BK20150271，主持 2016.01-2018.12，国家自然科学基金青年项目，编号：61501060，主持 |
