Min Tan is currently with School of Computer Science and Technology in Hangzhou Dianzi University (HDU), and a member of Media Inteligence Laboratory (CAMA-LAB), led by Prof. Jun Yu. She received the B.S. Degree in School of Mathematical Science and Computing Technology from Central South University, Changsha, China and Ph.D. Degree in College of Compute Science and Technology from Zhejiang University, Hangzhou, China, in 2009 and 2015, respectively. Her Ph.D. advisor is Prof. Zhaohui Wu, and she is co-advised by Prof. Gang Pan and Dr. Yueming Wang. From Jun. 2013 to Feb. 2014, she was an Intern in Prof. Yi Ma’s Visual Computing group in MSRA and advised by Dr. Baoyuan Wang.

She mainly applies machine learning techniques to computer vision problems. Her research interests include object detection, image classification, user click prediction, multi-task learning, deep learning, etc. Her research results have expounded in 10+ publications at prestigious journals and conferences, such as IEEE T-ITS, Neurocomputing, IEEE ICME, etc. He served for a number of journals and conferences, including IEEE Trans. on Image Processing (TIP), IEEE Trans. on Cybernetics (TCYB), ACM Transactions on Intelligent Systems and Technology (ACM TIST), IEEE Trans. on (T-ITS), Neurocomputing, etc.

Latest News

Feb. 2017
Paer submitted to ICME was accepted
Paper titled "Fine-grained Image Recognition via Weakly Supervised Click Data Guided Bilinear CNN model" was accepted by IEEE International Conference on Multimedia & Expo (ICME), 2017.
July. 2016
Supported by the China National Natural Science Foundation
Supported by the China National Natural Science Foundation (for Young Scholars), Jan. 2017 - Dec. 2019, PI: Min Tan.
Feb. 2016
Paper submitted to IEEE Transactions on Intelligent Transportation Systems was accepted
Paper titled "Weakly Supervised Metric Learning for Traffic Sign Recognition in a LIDAR-Equipped Vehicle" was accepted by the SCI indexed journal IEEE Transactions on Intelligent Transportation Systems.
May. 2015
Paper submitted to Neurocomputing was accepted
Paper titled "Robust object recognition via weakly supervised metric and template learning" was accepted by the SCI indexed journal Neurocomputing.