杨彪
职称、学历
单位 常州大学
城市 邮编 常州，213016
办公电话：**
E-MAIL:yb**@cczu.edu.cn

教育背景:
东南大学 工学博士

工作履历:
2014.06 -至今 常州大学 讲师

主授课程:
电机学 电机拖动基础 运动控制系统

研究领域:
人工智能 计算机视觉 机器学习



学术成果:
1.Yang B, Cao J, Wang N, et al. 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.
2.Yang B, Cao J, Wang N, et al. Counting challenging crowds robustly using a multi-column multi-task convolutional neural network[J]. Signal Processing: Image Communication, 2018, 64: 118-129.
3.Yang B, Cao J, Liu X, et al. Edge computing-based real-time passenger counting using a compact convolutional neural network[J]. Neural Computing and Applications, 2018: 1-13.
4.Yang B, Cao J, Ni R, et al. Anomaly detection in moving crowds through spatiotemporal autoencoding and additional attention[J]. Advances in Multimedia, 2018, 2018.
5.Yang B, Cao J, Zhou T, et al. Exploration of Neural Activity under Cognitive Reappraisal Using Simultaneous EEG-fMRI Data and Kernel Canonical Correlation Analysis[J]. Computational and mathematical methods in medicine, 2018, 2018.
6.Yang B, Cao J, Ni R, et al. Facial expression recognition using weighted mixture deep neural network based on double-channel facial images[J]. IEEE Access, 2018, 6: 4630-4640.
7.Yang B, Cao J M, Wang N, et al. Cross-scene counting based on domain adaptation-extreme learning machine[J]. IEEE Access, 2018, 6: 17029-17038.
8.Yang B, Zhang Y, Cao J, et al. On road vehicle detection using an improved faster RCNN framework with small-size region up-scaling strategy[C]//Pacific-Rim Symposium on Image and Video Technology. Springer, Cham, 2017: 241-253.
9.Cao J, Yang B, Zhang Y, et al. Crowd Counting from a Still Image Using Multi-scale Fully Convolutional Network with Adaptive Human-Shaped Kernel[C]//Pacific-Rim Symposium on Image and Video Technology. Springer, Cham, 2017: 227-240.
10.Yang B, Cao J, Zou L. Moving object detection based on on-line block-robust principal component analysis decomposition[J]. Modern Physics Letters B, 2017, 31(19-21): **.
11. Counting congested crowds under wild conditions with a multi-task Inception network[J].Communications in Information and Systems,2017,17(1):1-24.
12.Yang B, Cao J M, Jiang D P, et al. Facial expression recognition based on dual-feature fusion and improved random forest classifier[J]. Multimedia Tools and Applications, 2017: 1-23.
13.Yang B, Zou L. Robust foreground detection using block-based RPCA[J]. Optik, 2015, 126(23): 4586-4590.
14.Yang B, Lin G, Zhang W. An occlusion-adaptive tracker based on sparse representation using alternating direction method of multipliers[J]. Optik-International Journal for Light and Electron Optics, 2014, 125(13): 3055-3059.
15.Yang B, Lin G. Human appearance matching based on major color and spatio-texture features across disjoint camera views[M]//Foundations and Practical Applications of Cognitive Systems and Information Processing. Springer, Berlin, Heidelberg, 2014: 261-273.
16.Yang B, Lin G, Zhang W. Integration of Lab model and EHOG for human appearance matching across disjoint camera views[J]. Journal of Southeast University, 2012, 28(4): 422-427.
17.Lin G, Yang B, Zhang W. Human tracking in camera network with non-overlapping FOVs[J]. Journal of Southeast University, 2012, 28(2): 156-163.
18.Wang N, Song A, Yang B. The effect of time-delayed feedback on logical stochastic resonance[J]. The European Physical Journal B, 2017, 90(6): 117.

专利成果：
1.一种利用多尺度多任务卷积神经网络对静止图像进行人群计数的方法
2.面向面部表情识别的双通道卷积神经网络
3.一种基于长短期记忆-加权神经网络对视频人群计数的方法
4.加权卷积自编码长短期记忆网络人群异常检测方法
5.一种无重叠视域多摄像机监控网络拓扑自适应学习方法
6.一种基于修正加权二部图的无重叠视域目标匹配方法

研究项目:
1.国家自然科学基金：复杂公共环境下群体行为尺度自适应建模与特定异常行为识别算法研究（主持）
2.江苏省科技厅青年基金：复杂公共环境下特定群体异常行为识别算法研究（主持）
3.江苏省高校自然科学研究面上项目：深度卷积网络在多传感器融合车辆检测中的应用研究（主持）