Paper
23 May 2023 Remote sensing image target detection algorithm based on CenterNet
Zhiyuan Wang, Jin Duan, Tao Wu, Lin Li, Likun Huang
Author Affiliations +
Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126451P (2023) https://doi.org/10.1117/12.2681141
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China
Abstract
Aiming at the problems of small target scale, vulnerable to background interference and insufficient feature utilization in remote sensing image target detection task, a single stage target detection algorithm based on feature enhancement and feature fusion is proposed. Based on CenterNet, a feature enhancement module is designed, which enriches and strengthens the features of small targets and solves the problem of low accuracy caused by small targets and background interference. Then BiFPN mini multi-scale feature fusion structure is used to strengthen the feature expression ability of the target and solve the problem of insufficient feature utilization. This algorithm is implemented in the average detection accuracy on UCAS_AOD dataset reaches 84.9%. The experimental results show that the improved measures in this paper effectively improve the target detection accuracy for remote sensing images.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhiyuan Wang, Jin Duan, Tao Wu, Lin Li, and Likun Huang "Remote sensing image target detection algorithm based on CenterNet", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126451P (23 May 2023); https://doi.org/10.1117/12.2681141
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KEYWORDS
Detection and tracking algorithms

Convolution

Remote sensing

Feature fusion

Target detection

Feature extraction

Small targets

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