Infrared small target detection based on region proposal and CNN classifier

Fan, Mingming; Tian, Si; Li, Kai; Zhao, Jiaxin; Li, Yunsong

doi:10.1007/s11760-021-01936-z

Cited by 18 publications

(10 citation statements)

References 26 publications

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“…The pre-trained YOLOv5 algorithm was trained on 500 small target datasets according to four schemes: no optimization scheme, adding CBAM, Bi-FPN replacing PAN-Net, and combining CBAM with Bi-FPN. For a better comparison, the Faster R-CNN algorithm 9,10,11 is also added. The quality and efficiency of these five schemes are shown in Table 1.…”

Section: Experiments 41 Experimental Resultsmentioning

confidence: 99%

Aerial small target detection algorithm based on YOLOv5

Wang,

Xing,

Hao

et al. 2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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As a technology that has been developed for more than ten years, small target detection has been very mature at the technical level. A large number of target detection methods such as Faster R-CNN, RetinaNet, and YOLO have emerged that can be used in the industry. However, the problem of poor detection performance of small targets has not been completely solved so far. This paper focuses on the research and analysis of the optimization of the YOLOv5 algorithm around four optimization schemes, so that the sensitivity and fineness of the YOLOv5 algorithm for small target detection have been significantly improved. The experimental results show that the CBAM module can provide more small target feature information in the feature information extraction link, thereby increasing the efficiency of the algorithm for small target detection, and the replacement of the PAN-Net structure with the Bi-FPN structure can be used in the feature information feedback link. Reduce its loss, thereby increasing the efficiency of the algorithm, and the two schemes can be well combined to further improve the detection effect of small targets.

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Section: Experiments 41 Experimental Resultsmentioning

confidence: 99%

Aerial small target detection algorithm based on YOLOv5

Wang,

Xing,

Hao

et al. 2023

Third International Conference on Signal Image Processing and Communication (ICSIPC 2023)

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“…Optimized region proposal: Fan et al [20] proposed an infrared small-object detection method based on region proposal and a CNN module to separate real objects from the background and significantly reduce the false alarm rate caused by complex background clutter. First, the small-object intensity is enhanced based on the local intensity characteristics.…”

Section: Infrared Small-object Detection Methods Based On Cnnmentioning

confidence: 99%

“…Many researchers have been inspired by small-object detection methods and have proposed detection models suitable for small objects. The optimized methods of these models can be categorized into spatial-temporal information fusion [15][16][17], residual/background information prediction [18,19], optimized region proposal [20,21], and multiscale information fusion [22][23][24][25]. The spatial-temporal information fusion method reduces static noise by combining adjacent frames in an infrared image sequence.…”

Section: Introductionmentioning

confidence: 99%

IRSDet: Infrared Small-Object Detection Network Based on Sparse-Skip Connection and Guide Maps

2022

Electronics

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Detecting small objects in infrared images remains a challenge because most of them lack shape and texture. In this study, we proposed an infrared small-object detection method to improve the capacity for detecting thermal objects in complex scenarios. First, a sparse-skip connection block is proposed to enhance the response of small infrared objects and suppress the background response. This block is used to construct the detection model backbone. Second, a region attention module is designed to emphasize the features of infrared small objects and suppress background regions. Finally, a batch-averaged biased classification loss function is designed to improve the accuracy of the detection model. The experimental results show that the proposed small-object detection framework significantly increases precision, recall, and F1-score, showing that, compared with the current advanced detection models for small-object detection, the proposed detection framework has better performance in infrared small-object detection under complex backgrounds. The insights gained from this study may provide new ideas for infrared small object detection and tracking.

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“…The utilization of target infrared radiation characteristics as a detection technique has found extensive application in reconnaissance and detection [1][2][3][4] . Furthermore, when the military vehicle is detected and identified, it usually becomes more vulnerable.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the infrared radiation characteristics of a vehicle model under sunny weather

Ren,

Li,

Chen

et al. 2024

Fifth International Conference on Optoelectronic Science and Materials (ICOSM 2023)

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Military vehicles are vulnerable to hostile infrared reconnaissance in the battlefield. So, it is essential to investigate the infrared radiation characteristics and camouflage methods of the vehicle. This paper proposes a method utilizing heat exchange theory to study the temperature distribution and the infrared radiation characteristics of a simplified vehicle prototype. The research reveals that the temperature distribution and the infrared radiation distribution are different for all six surfaces, which are mainly influenced by internal heat source, air temperature and solar radiation. This study is expected to provide useful guidance to vehicle camouflage pattern design.

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Infrared small target detection based on region proposal and CNN classifier

Cited by 18 publications

References 26 publications

Aerial small target detection algorithm based on YOLOv5

Aerial small target detection algorithm based on YOLOv5

IRSDet: Infrared Small-Object Detection Network Based on Sparse-Skip Connection and Guide Maps

Simulation of the infrared radiation characteristics of a vehicle model under sunny weather

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