Gaussian-IoU loss: Better learning for bounding box regression on PCB component detection

作者：

Highlights：

• A novel Gaussian intersection over union is designed for box regression.

• An adaptive weight strategy is introduced for loss function.

• A new dataset of circuit board components (PCBC dataset) is created.

• The proposed method achieves good performance on COCO dataset and PCBC dataset.

摘要

•A novel Gaussian intersection over union is designed for box regression.•An adaptive weight strategy is introduced for loss function.•A new dataset of circuit board components (PCBC dataset) is created.•The proposed method achieves good performance on COCO dataset and PCBC dataset.

论文关键词：Object detection,PCB-components,Industrial inspection,Box regression,Gaussian IoU

论文评审过程：Received 25 March 2021, Revised 19 October 2021, Accepted 29 October 2021, Available online 12 November 2021, Version of Record 23 November 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.116178