Small-Target Detection Based on an Attention Mechanism for Apron-Monitoring Systems

Author:

Liu Hao1,Ding Meng1ORCID,Li Shuai1,Xu Yubin2,Gong Shuli1,Kasule Abdul1

Affiliation:

1. College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

2. China Academy of Civil Aviation Science and Technology, Beijing 100028, China

Abstract

Small-target detection suffers from the problems of low average precision and difficulties detecting targets from airport-surface surveillance videos. To address this challenge, this study proposes a small-target detection model based on an attention mechanism. First, a standard airport small-target dataset was established, where the absolute scale of each marked target meets the definition of a small target. Second, using the Mask Scoring R-CNN model as a baseline, an attention module was added to the feature extraction network to enhance its feature representation and improve the accuracy of its small-target detection. A multiscale feature pyramid fusion module was used to fuse more detailed shallow information according to the feature differences of diverse small targets. Finally, a more effective detection branch structure is proposed to improve detection accuracy. Experimental results verify the effectiveness of the proposed method in detecting small targets. Compared to the Mask R-CNN and Mask Scoring R-CNN models, the detection accuracy of the proposed method in two-pixel intervals with the lowest rate of small targets increased by 10%, 3.04% and 16%, 15.15%, respectively. The proposed method proved to have a higher accuracy and be more effective at small-target detection.

Funder

National Natural Science Foundation of China

Opening Project of Civil Aviation Satellite Application Engineering Technology Research Center

Nanjing University of Aeronautics and Astronautics Innovation Program Project

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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