The Embedded Deep Learning and Visual Analysis Laboratory belongs to School of Information Science and Technology of Fudan University, Shanghai. The lab focuses on the research of deep learning algorithms for mobile and AI chipset based applications. The team has developed a number of state-of-the-art new CNN architectures for object detection and classification, under the conditions of weakly supervised and computing resource constrained scenarios.

Dr. Chen Tao, the PI  of the laboratory, received his Ph.D. from Nanyang Technological University in Singapore in 2012. At the beginning of 2018, he was selected into the National High Level Oversea Talent Plan, and joined Fudan University as a tenure_track Professor. Before joining Fudan, he worked at the top research institutions such as the Singapore Science and Technology Bureau, the Singapore Intelligent Robot Laboratory, and the Singapore Institute for Infocomm Research. He has undertaken and participated in a series of projects from the Singapore government and enterprises. In addition, Dr. Chen Tao has also worked on the research and development of AI chipsets at the AI lab of Huawei Asia Pacific Research Institute from 2017 to 2019, and have a number of AI products. 

Computer Vision, deep learning, lightweight neural network design for AI chipsets

2019-Now, Fudan University,                                                          Tenture_track Professor

2017-2019, Huawei Singapore Research Center                                        Senior Scientist

2013-2017, Institute for Infocomm Research, A*STAR, Singapore,                 Scientist

2008-2012, Nanyang Technological University,                                                PhD

2006-2008, Zhejiang University,                                                                        M.Eng

2002-2006, Shandong University,                                                                     Bachelor

[J21] W. Wang, Q. Sun, Y.Fu, T. Chen, C. Cao, Z. Zheng, G. Xu, H. Qiu, Y. Jiang and X. Xue, "Comp-GAN: Compositional Generative Adversarial Network in Synthesizing and Recognizing Facial Expression," ACM International Conference on Multimedia (ACM'MM, Full Paper), Nice, France, 2019.

[J20] T. Chen, S. Lu, J.Fan*, "SS-HCNN: Semi-Supervised Hierarchical Convolutional Neural Network for Image Classification," IEEE Transactions on Image Processing (T-IP), 28(5):2389-2398, 2019.

[J19] T. Chen, S. Lu, J. Fan, " S-CNN: Subcategory-aware convolutional networks for object detection ," IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 40(10):2522-2528, 2018.

[J18] J. Fan, T. Chen* (Corresponding Author), S. Lu, " Superpixel Guided Deep-Sparse-Representation Learning For Hyperspectral Image Classification, " IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 28(11):3163-3173, 2017.

[J17] T. Chen, S. Lu, “Subcategory-aware feature selection and SVM optimization for automatic aerial image based oil spill inspection," IEEE Transactions on GeoScience and Remote Sensing (T -GRS ), 55(9): 5264-5273, 2017.

[J16] Fan J. Y. , T. Chen, S. Lu, “ Unsupervised Feature Learning For Land -Use Scene Recognition," IEEE Transactions on GeoScience and Remote Sensing (T -GRS ), 55(4):2250-2261, 2017.

[J15] T. Chen, S. Lu, “Object-level motion detection from moving optic cameras,” IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 27(11):2333-2343, 2017.

[J14] T. Chen, S. Lu, “Accurate and Efficient Traffic Sign Detection Using Discriminative Adaboost and Support Vector Regression,” IEEE Transactions on Vehicular Technology (T-VT), vol. 65, pp.4006-4015, 2016.

[J13] T. Chen, S. Lu, “Robust vehicle detection and viewpoint estimation with soft discriminative mixture mode ,” IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), vol.27, no. 2, pp. 394-403,  Feb 2017.

[J12] J. W. Cao, T. Chen, J. Y. Fan, "Landmark Recognition with Compact BoW Histogram and Ensemble ELM," Multimedia Tools and Applications (MTAP), pp. 1-19, 2015.

[J11] J. Y. Fan, T. Chen, C.C. Kot, “EXIF-white balance recognition for image forensic analysis,” Multidimensional Systems and Signal Processing (MSSP),  pp. 1-21, 2016.

[J10] T. Chen, S. Lu, J. Y. Fan, “Context-Aware Vocabulary Tree for Mobile Landmark Recognition,” Journal of Visual Communication and Image Representation (JVCIR), vol. 30, pp. 289-298, 2015.

[J9]T. Chen, K.-H. Yap, “Discriminative Soft Bag-of-Visual Phrase for Mobile Landmark Recognition,” IEEE Transactions on Multimedia (T-MM), vol. 16, pp.612-622, Apr 2014.

[J8] T. Chen, K.-H. Yap, “Context-Aware Discriminative Vocabulary Learning for Mobile Landmark Recognition,” IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), vol.23, pp. 1611 - 1621, 2013.

[J7] T. Chen, K.-H. Yap, “Discriminative BoW Framework for Mobile Landmark Recognition,” IEEE Transactions on Systems, Man and Cybernetics (T-SMC), Part B, vol. 44, pp. 695-706, 2013.

[J6] S. Lu, T. Chen, S. Tian, J.-H. Lim, T.- C. Lim, "Scene Text Extraction based on Edges and Support Vector Regression," International Journal on Document Analysis and Recognition (IJDAR), vol. 18, pp. 125-135, 2015.

 [J5] T. Chen, K.-H. Yap, and L.-P. Chau, "Integrated Content and Context Analysis for Mobile Landmark Recognition," IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), vol. 21, pp. 1476 - 1486, 2011.

[J4] K.-H. Yap, T. Chen, Z. Li, and K. Wu, “A Comparative Study of Mobile-based Landmark Recognition,” IEEE Intelligent Systems (IS), vol. 25,  no.1,  pp. 48-57, 2010. （First Author is PhD supervisor）

 [J3] T. Chen, Z. G. Fang, J. Xu, “A Multi-Channel Identity Verification System based on Face and Voice,” Journal of Shandong University (Engineering Science), vol. 38, no. 2, pp. 56-60, 2008.

[J2] T. Chen, Z. G. Fang, J. Xu, “A Speaker Identity System based on Verification Mode," Journal of Ergonomics, vol. 14, no. 1, pp. 42-44, 2008.

[J1] Z. P. Lin, J. W. Cao, T. Chen, “Extreme Learning Machine on High Dimensional and Large Data Applications,” Mathematical Problems in Engineering, pp. 1-2, 2015.