Bio
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I'm a Research Engineer working on deep learning and computer vision at Snap Inc. Before joining Snap, I worked on GluonCV at Amazon AI. I also developed Echo Look and Amazon Cloud Cam's deep learning model at Amazon Lab126's computer vision/machine learning team. I received my bachelor degree in computer science from University of Washington in 2015. I have also worked with sparse data during my two internships at Google, and Amazon. |
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ResNeSt: Split-Attention Network
Hang Zhang,
Chongruo Wu,
Zhongyue Zhang,
Yi Zhu,
Haibin Lin,
Zhi Zhang,
Yue Sun,
Tong He,
Jonas Mueller,
R. Manmatha,
Mu Li,
Alex SmolaarXiv PyTorch MXNet |
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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
Jian Guo,
He He,
Tong He,
Leonard Lausen,
Mu Li,
Haibin Lin,
Xingjian Shi,
Chenguang Wang,
Junyuan Xie,
Sheng Zha,
Aston Zhang,
Hang Zhang,
Zhi Zhang,
Zhongyue Zhang,
Shuai Zheng,
Yi ZhuJournal of Machine Learning Research (JMLR), 2020 arXiv JMLR code |
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Bag of Freebies for Training Object Detection Neural Networks
Zhi Zhang,
Tong He,
Hang Zhang,
Zhongyue Zhang,
Junyuan Xie,
Mu LiarXiv code |
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Bag of Tricks for Image Classification with Convolutional Neural Networks
Tong He,
Zhi Zhang,
Hang Zhang,
Zhongyue Zhang,
Junyuan Xie,
Mu LiIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 arXiv code |
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Context Encoding for Semantic Segmentation
Hang Zhang,
Kristin Dana,
Jianping Shi,
Zhongyue Zhang,
Xiaogang Wang,
Ambrish Taygi,
Amit AgarwalIEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018 (Oral) arXiv CVPR code |
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Megaman: scalable manifold learning in python
James McQueen,
Marina Meila,
Jake VanderPlas,
Zhongyue ZhangJournal of Machine Learning Research (JMLR), 2016 arXiv JMLR code |
| Megaman: a scalable manifold learning in python | |
| Gluon-CV: a Deep Learning Toolkit for Computer Vision | |
| AutoGluon: AutoML Toolkit for Deep Learning |