Novel transformer models for wheat disease classification with explainable insights

Today's article comes from the Journal of Big Data. The authors are Abdelatey et al., from Menoufia University, in Egypt. In this paper they're building a computer vision system specifically for detecting diseases in wheat leaves. It combines two architectures: the Swin Transformer and the DeiT, and fuses the features they extract into a single hybrid model.

DOI: 10.1186/s40537-025-01353-w