Electronics Optics & Control, Volume. 30, Issue 4, 28(2023)

Deep Learning Single-Stage Infrared Aircraft Detection Based on Improved Regression Loss

CAO Zixuan, LIU Gang, ZHANG Wenbo, LIU Sen, and LIU Zhonghua
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    Aiming at the characteristics that the accuracy of object detection and positioning is affected by the loss function of frame regression, a frame regression loss function IAIoU (Included Aspect-ratio IoU) based on IoU (Intersection over Union) is designed.Two optimization terms are designed for this loss.There is the ratio of the difference between the union and intersection area of the prediction box and the labeled box to the smallest enclosed area of the two boxes, as well as the ratio of the difference to the square of the smallest enclosed area of the two boxes.The sum of the two ratios is used as the first optimization term, which avoids the degeneration of loss function when the two boxes are included.The difference between the aspect ratios of the two boxes is adopted as the second optimization term to generate a prediction box that is closer to the labeled box.The designed loss is applied to the single-stage detection algorithm YOLOv3 and verified on the infrared aircraft data set.The mAP reaches 92.17%, which is 1.37% higher than that of the original YOLOv3.

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    CAO Zixuan, LIU Gang, ZHANG Wenbo, LIU Sen, LIU Zhonghua. Deep Learning Single-Stage Infrared Aircraft Detection Based on Improved Regression Loss[J]. Electronics Optics & Control, 2023, 30(4): 28

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    Paper Information

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    Received: Feb. 23, 2022

    Accepted: --

    Published Online: Jun. 12, 2023

    The Author Email:

    DOI:10.3969/j.issn.1671-637x.2023.04.006

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