现代电子技术2024，Vol.47Issue(9)：53-58,6.DOI:10.16652/j.issn.1004-373x.2024.09.010
KoiU-Net:基于多特征增强融合的纺锤形鱼类图像分割方法
KoiU-Net:A fusiform fish image segmentation method based on multi-feature enhancement fusion
朱珈缘 1孟娟 1杜海 2马媛媛 1曹静雯1
作者信息
- 1. 大连海洋大学 信息工程学院,辽宁 大连 116023
- 2. 大连理工大学 海岸和近海工程国家重点实验室,辽宁 大连 116024
- 折叠
摘要
Abstract
In view of the blurred edges and vague features in the fusiform fish image segmentation task,a multi-feature enhancement and fusion based fusiform fish image segmentation network KoiU-Net is proposed.On the basis of the classical U-Net model,a multi-scale feature cross perception module and a multi-scale feature fusion module are designed to enhance the processing capability of fusiform fish features,so as to cope with the problems of blurred edges and complex features in the segmentation of fusiform fish image.The multi-scale upsampling module is designed to extract finer feature information.Experiments on the fusiform fish image dataset show that the KoiU-Net achieves significant improvement in segmentation accuracy,averaging 98.63%,in comparison with the other segmentation networks such as the original U-Net.The effectiveness of each design module is also verified by ablation experiments,and the multi-scale feature cross perception module plays a key role in improving the segmentation performance.This study provides effective technical support for further implementation of fusiform fish growth state monitoring and lays the foundation for the further development in this field.关键词
深度学习/图像分割/分割精度/纺锤形鱼/U-Net/多尺度特征融合Key words
deep learning/image segmentation/segmentation accuracy/fusiform fish/U-Net/multi-scale feature fusion分类
电子信息工程引用本文复制引用
朱珈缘,孟娟,杜海,马媛媛,曹静雯..KoiU-Net:基于多特征增强融合的纺锤形鱼类图像分割方法[J].现代电子技术,2024,47(9):53-58,6.
