APHS-YOLO: A Lightweight Model for Real-Time Detection and Classification of Stropharia Rugoso-Annulata

• Published in: Foods Vol. 13; no. 11; p. 1710
• Main Authors: Liu, Ren-Ming, Su, Wen-Hao
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 29.05.2024; MDPI
• Subjects: Accuracy; Algorithms; automatic sorting; Classification; Convolution; Datasets; Deep learning; Feature extraction; Feature selection; Forest farming; Frames per second; Grading (Commerce); high-level screen feature pyramid; Identification and classification; knowledge distill; lightweight model; Machine learning; Methods; Modules; Mushrooms; Object recognition; Real time; Stropharia rugoso-annulata; Technology application; Varieties; Vision systems; China; automatic sorting; high-level screen feature pyramid; knowledge distill; Stropharia rugoso-annulata; lightweight model

The classification of Stropharia rugoso-annulata is currently reliant on manual sorting, which may be subject to bias. To improve the sorting efficiency, automated sorting equipment could be used instead. However, sorting naked mushrooms in real time remains a challenging task due to the difficulty...