Rice Organ Segmentation. 
We validate on another crop variety to justify the cross-species generalization of the backbone. Our team developed the RiceSEG image segmentation dataset through international collaboration, focusing on rice fields with weeds and duckweed backgrounds. The images were collected between 2012 and 2023 by 10 institutions from 10 locations across five countries, including China, Japan, India, the Philippines, and Tanzania, covering over 1,000 rice varieties. The images were captured using various camera types, such as digital SLRs, portable action cameras, and smartphones. The cameras were positioned 1-2 meters above the canopy and oriented toward the canopy in different directions (0°-90°). The dataset has 2,462 training images and 616 testing images. 

Zhou, J. et al. Global Rice Multiclass Segmentation Dataset (RiceSEG): Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms. Plant Phenomics 100099 (2025) doi:10.1016/j.plaphe.2025.100099.