Open AccessResearch on the Algorithm of Detection for Small and Weak Target Based on the Mechanism of High-Resolution Amplification
Author(s) -
Xiangdong Cheng,
Lili Sun,
Yachong Tian
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2025/1/012031
Subject(s) - computer science , artificial intelligence , resolution (logic) , high resolution , algorithm , mechanism (biology) , selection (genetic algorithm) , information gain , pattern recognition (psychology) , machine learning , data mining , remote sensing , physics , geography , quantum mechanics
Aiming at the problem that the existing target detection framework based on big data and deep learning has poor recognition effect for small and weak targets with low resolution in complex scenes, in this paper, we improve the small targets detection accuracy and speed, based on the FCOS algorithm for target detection and the mechanism of high resolution amplification. The basic principle is to increase amplification precision gain regression network (R-NET) and amplification region selection algorithm, on the basis of enhanced learning. The former learns the correlation between coarse and fine detection, and the latter calculates the information gain of the amplified region. The results show that this method can detect small and weak targets in complex environment.