Fusing deep learning features of triplet leaf image patterns to boost soybean cultivar identification

Bin Wang, Hao Li, Jiawei You, Xin Chen, Xiaohui Yuan, Xianzhong Feng

Abstract: Highlights•This research focuses on soybean cultivar identification which is known as a very fine-grained classification problem.•The first attempt on fusing deep features of triplet leaf image patterns is reported.•Two deep feature fusion methods, distance fusion and classifier fusion, are proposed.•A novel fine-tuning strategy that addresses the issue of few-shot soybean leaf image classification is designed.•The proposed method achieves an exciting accuracy of 83.55% on classifying 200 soybean cultivars.