S-FPN: A shortcut feature pyramid network for sea cucumber detection in underwater images

作者：

Highlights：

• An underwater image dataset of sea cucumber was created and annotated with rectangular boxes.

• A detection network S-FPN, introducing shortcut connections to the feature pyramid, was proposed.

• A new Piecewise Focal Loss function was created to alleviate the problem of class imbalance in object detection.

摘要

•An underwater image dataset of sea cucumber was created and annotated with rectangular boxes.•A detection network S-FPN, introducing shortcut connections to the feature pyramid, was proposed.•A new Piecewise Focal Loss function was created to alleviate the problem of class imbalance in object detection.

论文关键词：Sea cucumber,Deep learning,Computer vision,Underwater object detection

论文评审过程：Received 25 September 2020, Revised 21 April 2021, Accepted 28 May 2021, Available online 4 June 2021, Version of Record 12 June 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115306