Computer Vision-Based Deep Learning Modeling for Salmon Part Segmentation and Defect Identification

Accurate cutting of salmon parts and surface defect detection are the key steps to enhance the added value of its processing. At present, mainstream manual inspection methods have low accuracy and efficiency, making it difficult to meet the demands of industrialized production. A machine vision inspection method based on a two-stage fusion network is proposed in this paper, aiming to achieve accurate cutting of salmon parts and efficient recognition of defects. The fish body image is collected...

food science, nutrition, processing, quality, sensory
Computer Vision-Based Deep Learning Modeling for Salmon Part Segmentation and Defect Identification