3 papers
cs.CV2020
PolarDet: A Fast, More Precise Detector for Rotated Target in Aerial Images
Pengbo Zhao, Zhenshen Qu, Yingjia Bu +3
Fast and precise object detection for high-resolution aerial images has been a challenging task over the years. Due to the sharp variations on object scale, rotation, and aspect ra…
cs.CV2020
Deep Active Learning for Remote Sensing Object Detection
Zhenshen Qu, Jingda Du, Yong Cao +2
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…
cs.CV2018
PartsNet: A Unified Deep Network for Automotive Engine Precision Parts Defect Detection
Zhenshen Qu, Jianxiong Shen, Ruikun Li +2
Defect detection is a basic and essential task in automatic parts production, especially for automotive engine precision parts. In this paper, we propose a new idea to construct a…