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Hang Zhao

Researcher at Tsinghua University

Publications -  108
Citations -  19405

Hang Zhao is an academic researcher from Tsinghua University. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 32, co-authored 83 publications receiving 12696 citations. Previous affiliations of Hang Zhao include Zhejiang University & Nvidia.

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Journal ArticleDOI

Millimeter Wave Mobile Communications for 5G Cellular: It Will Work!

TL;DR: The motivation for new mm-wave cellular systems, methodology, and hardware for measurements are presented and a variety of measurement results are offered that show 28 and 38 GHz frequencies can be used when employing steerable directional antennas at base stations and mobile devices.
Proceedings ArticleDOI

Scene Parsing through ADE20K Dataset

TL;DR: The ADE20K dataset, spanning diverse annotations of scenes, objects, parts of objects, and in some cases even parts of parts, is introduced and it is shown that the trained scene parsing networks can lead to applications such as image content removal and scene synthesis.
Journal ArticleDOI

Loss Functions for Image Restoration With Neural Networks

TL;DR: It is shown that the quality of the results improves significantly with better loss functions, even when the network architecture is left unchanged, and a novel, differentiable error function is proposed.
Posted Content

Scalability in Perception for Autonomous Driving: Waymo Open Dataset

TL;DR: This work introduces a new large scale, high quality, diverse dataset, consisting of well synchronized and calibrated high quality LiDAR and camera data captured across a range of urban and suburban geographies, and studies the effects of dataset size and generalization across geographies on 3D detection methods.
Journal ArticleDOI

Semantic Understanding of Scenes Through the ADE20K Dataset

TL;DR: The ADE20K dataset as discussed by the authors contains 25k images of complex everyday scenes containing a variety of objects in their natural spatial context, on average there are 19.5 instances and 10.5 object classes per image.