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View all- Li YZhang YYang CChen Y(2025) UMS -ODNet: Unified-scale domain adaptation mechanism driven object detection network with multi-scale attention Neural Networks10.1016/j.neunet.2024.106890181(106890)Online publication date: Jan-2025
An Infrared Small Target Detection Method Using Segmentation Based Region Proposal and CNN
Authors: 
Shan Wen, Kai Liu, Shaoqing Tian, Mingming Fan, Lin YanAuthors Info & Claims
Shan Wen, Kai Liu, Shaoqing Tian, Mingming Fan, Lin YanAuthors Info & ClaimsPages 153 - 160
Abstract
Previous infrared small target detection approaches mainly solve the problem of detecting small target in sky background with strong cloud occlusion. However, these methods hardly exclude the negative objects other than cloud that cause false alarms. To address this problem, we propose an infrared small target detection framework using segmentation based region proposal and Convolution Neural Network (SCNN). In specific, an improved segmentation algorithm is used to obtain the salient regions from the background as the proposals. To reduce the high false alarms from proposals, a lightweight CNN is used to classify these regions and make final predictions. Owning to the lack of current public infrared small target datasets, a new infrared dataset is proposed in this paper. The experimental results demonstrate that the proposed method has a good performance in detection rate and false alarm rate.
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Published In
February 2021
601 pages
ISBN:9781450389310
DOI:10.1145/3457682
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Published: 21 June 2021
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- National Natural Science Foundation of China
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ICMLC 2021
ICMLC 2021: 2021 13th International Conference on Machine Learning and Computing
February 26 - March 1, 2021
Shenzhen, China
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View all- Li YZhang YYang CChen Y(2025) UMS -ODNet: Unified-scale domain adaptation mechanism driven object detection network with multi-scale attention Neural Networks10.1016/j.neunet.2024.106890181(106890)Online publication date: Jan-2025
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