T
Tony X. Han
Researcher at University of Missouri
Publications - 83
Citations - 8811
Tony X. Han is an academic researcher from University of Missouri. The author has contributed to research in topics: Computer science & Object detection. The author has an hindex of 28, co-authored 62 publications receiving 7688 citations. Previous affiliations of Tony X. Han include Baidu & University of Illinois at Urbana–Champaign.
Papers
More filters
End to end speech recognition in English and Mandarin
Dario Amodei,Rishita Anubhai,Eric Battenberg,Carl Case,Jared Casper,Bryan Catanzaro,Jingdong Chen,Mike Chrzanowski,Adam Coates,Greg Diamos,Erich Elsen,Jesse Engel,Linxi Fan,Christopher Fougner,Tony X. Han,Awni Hannun,Billy Jun,Patrick LeGresley,Libby Lin,Sharan Narang,Andrew Y. Ng,Sherjil Ozair,Ryan Prenger,Jonathan Raiman,Sanjeev Satheesh,David Seetapun,Shubho Sengupta,Yi Wang,Zhiqian Wang,Chong Wang,Bo Xiao,Dani Yogatama,Jun Zhan,Zhenyao Zhu +33 more
TL;DR: It is shown that an end-to-end deep learning approach can be used to recognize either English or Mandarin Chinese speech-two vastly different languages, and is competitive with the transcription of human workers when benchmarked on standard datasets.
Proceedings ArticleDOI
An HOG-LBP human detector with partial occlusion handling
TL;DR: By combining Histograms of Oriented Gradients (HOG) and Local Binary Pattern (LBP) as the feature set, this work proposes a novel human detection approach capable of handling partial occlusion and achieves the best human detection performance on the INRIA dataset.
Proceedings Article
Deep speech 2: end-to-end speech recognition in English and mandarin
Dario Amodei,Sundaram Ananthanarayanan,Rishita Anubhai,Jingliang Bai,Eric Battenberg,Carl Case,Jared Casper,Bryan Catanzaro,Qiang Cheng,Guoliang Chen,Jie Chen,Jingdong Chen,Zhijie Chen,Mike Chrzanowski,Adam Coates,Greg Diamos,Ke Ding,Niandong Du,Erich Elsen,Jesse Engel,Weiwei Fang,Linxi Fan,Christopher Fougner,Liang Gao,Caixia Gong,Awni Hannun,Tony X. Han,Lappi Vaino Johannes,Bing Jiang,Cai Ju,Billy Jun,Patrick LeGresley,Libby Lin,Junjie Liu,Yang Liu,Weigao Li,Xiangang Li,Dongpeng Ma,Sharan Narang,Andrew Y. Ng,Sherjil Ozair,Yiping Peng,Ryan Prenger,Sheng Qian,Zongfeng Quan,Jonathan Raiman,Vinay Rao,Sanjeev Satheesh,David Seetapun,Shubho Sengupta,Kavya Srinet,Anuroop Sriram,Haiyuan Tang,Liliang Tang,Chong Wang,Jidong Wang,Kaifu Wang,Yi Wang,Zhijian Wang,Zhiqian Wang,Shuang Wu,Likai Wei,Bo Xiao,Wen Xie,Yan Xie,Dani Yogatama,Bin Yuan,Jun Zhan,Zhenyao Zhu +68 more
TL;DR: In this article, an end-to-end deep learning approach was used to recognize either English or Mandarin Chinese speech-two vastly different languages-using HPC techniques, enabling experiments that previously took weeks to now run in days.
Proceedings Article
Learning efficient object detection models with knowledge distillation
TL;DR: This work proposes a new framework to learn compact and fast object detection networks with improved accuracy using knowledge distillation and hint learning and shows consistent improvement in accuracy-speed trade-offs for modern multi-class detection models.
Journal ArticleDOI
Residual Networks of Residual Networks: Multilevel Residual Networks
TL;DR: A novel residual network architecture, residual networks of residual networks (RoR) is proposed, to dig the optimization ability of residual Networks, where RoR substitutes optimizing residual mapping of residual mapping for optimizing original residual mapping.