Deep Active Learning for Remote Sensing Object Detection

17 Mar 2020 Zhenshen Qu Jingda Du Yong Cao Qiuyu Guan Pengbo Zhao

Recently, CNN object detectors have achieved high accuracy on remote sensing images but require huge labor and time costs on annotation. In this paper, we propose a new uncertainty-based active learning which can select images with more information for annotation and detector can still reach high performance with a fraction of the training images... (read more)

PDF Abstract

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper