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Infrared sequence small target detection based on memory pool
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Lin CHEN1, Chenqiang GAO1, Xiao HUANG2
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition) | 2025, 37(5) : 769 - 780
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Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition) | 2025, 37(5): 769-780
Artificial Intelligenceand Big Data
Infrared sequence small target detection based on memory pool
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Lin CHEN1, Chenqiang GAO1, Xiao HUANG2
Affiliations
  • 1School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
  • 2China Ship Development and Design Center, Wuhan 430064, P. R. China
doi: 10.3979/j.issn.1673-825X.202405060112
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To alleviate the scarcity of data, this paper collects and annotates two infrared tracking datasets for sequential small target detection, named ATR-ISTD and UAV-ISTD. This paper proposes a sequential small target detection network integrating a memory pool, which effectively utilizes the correlation information between frames before and after, reads memory information through memory matching between the query frame and the memory frame, and solves the problems of high false alarm and low accuracy in infrared small target detection under high clutter background. To reduce the loss of small target features caused by downsampling, a forward semantic guided fusion module(PSGF)is designed to integrate features of different scales. In the memory vector encoder, a pseudo label guided feature enhancement module(PLG-FE)is designed to enhance the local feature expression ability of small targets. Experimental results show that, compared with mainstream single-frame detection methods, the proposed method significantly reduces false alarm rates, achieving improvements of 16.87% and 10.49% on the ATR-ISTD and UAV-ISTD datasets, respectively. Target-level F1 scores increased by 4.89% and 6.54%, and pixel-level F1 scores improved by 7.69% and 11.63%.

infrared image  /  small target detection  /  memory pool  /  feature enhancement  /  feature fusion
Lin CHEN, Chenqiang GAO, Xiao HUANG. Infrared sequence small target detection based on memory pool[J]. Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition), 2025 , 37 (5) : 769 -780 . DOI: 10.3979/j.issn.1673-825X.202405060112
Year 2025 volume 37 Issue 5
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Article Info
doi: 10.3979/j.issn.1673-825X.202405060112
  • Receive Date:2024-05-06
  • Online Date:2026-04-16
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  • Received:2024-05-06
  • Revised:2025-06-30
Affiliations
    1School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, P. R. China
    2China Ship Development and Design Center, Wuhan 430064, P. R. China
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小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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