Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhou, Junchi, Wang, Haozhou, Kato, Yoichiro, Nampally, Tejasri, Rajalakshmi, P., Balram, M., Katsura, Keisuke, Lu, Hao, Mu, Yue, Yang, Wanneng, Gao, Yangmingrui, Xiao, Feng, Chen, Hongtao, Chen, Yuhao, Li, Wenjuan, Wang, Jingwen, Yu, Fenghua, Zhou, Jian, Wang, Wensheng, Hu, Xiaochun, Yang, Yuanzhu, Ding, Yanfeng, Guo, Wei, Liu, Shouyang
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Image and Video Processing Artificial Intelligence Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
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Accesso online

https://arxiv.org/abs/2504.02880