1 code implementation • ECCV 2020 • Kun Ding, Guojin He, Huxiang Gu, Zisha Zhong, Shiming Xiang, Chunhong Pan
State-of-the-art object detectors exploit multi-branch structure and predict objects at several different scales, although substantially boosted accuracy is acquired, low efficiency is inevitable as fragmented structure is hardware unfriendly.
no code implementations • 25 Jan 2021 • Peng Liu, Lizhe Wang, Guojin He, Lei Zhao
Which samples should be labelled in a large data set is one of the most important problems for trainingof deep learning.
no code implementations • 7 May 2018 • Tengfei Long, Zhaoming Zhang, Guojin He, Weili Jiao, Chao Tang, Bingfang Wu, Xiaomei Zhang, Guizhou Wang, Ranyu Yin
Heretofore, global burned area (BA) products are only available at coarse spatial resolution, since most of the current global BA products are produced with the help of active fire detection or dense time-series change analysis, which requires very high temporal resolution.