NGIoU Loss: Generalized Intersection over Union Loss Based on a New Bounding Box Regression
نویسندگان
چکیده
Loss functions, such as the IoU function and GIoU (Generalized Intersection over Union) have been put forward to replace regression loss functions commonly used in calculation. alleviates vanishing gradient case of non-overlapping, but it will completely degenerate into when bounding boxes overlap totally, which fails achieve optimization effect. To solve this problem, some improvements are proposed paper on basis function, taking account rate complete boxes. In PASCAL VOC data, experimental results demonstrate that AP NGIoU YOLOv4 model is 47.68%, 1.15% higher than highest map value 86.79% YOLOv5 model.
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ژورنال
عنوان ژورنال: Applied sciences
سال: 2022
ISSN: ['2076-3417']
DOI: https://doi.org/10.3390/app122412785