Detection of surface defects for maize seeds based on YOLOv5

2024/01/04 by Yu Xia, Tianci Che, Jingwu Meng +5
Agricultural and Biological Sciences · Chemistry · Engineering · #Industrial Vision Systems and Defect Detection #Smart Agriculture and AI #Spectroscopy and Chemometric Analyses

paper · doi:10.1016/j.jspr.2023.102242

openalex publication_date 2024/01/04 · crossref created 2024/01/04 · crossref issued 2024/02/01 · crossref published 2024/02/01 · crossref published-print 2024/02/01 · crossref deposited 2024/03/13 · openalex created_date 2025/10/10 · crossref indexed 2026/07/31 · openalex updated_date 2026/08/01

Citations

• Recent advances in convolutional neural networks
• Seed germination and vigor: ensuring crop sustainability in a changing climate
• Image classification and adversarial robustness analysis based on hybrid quantum–classical convolutional neural network
• Identifying common stored product insects using automated deep learning methods