2 papers
eess.IV2025
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
Junchi Zhou, Haozhou Wang, Yoichiro Kato +21
Developing computer vision-based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Am…
cs.CV2024
PanicleNeRF: low-cost, high-precision in-field phenotypingof rice panicles with smartphone
Xin Yang, Xuqi Lu, Pengyao Xie +6
The rice panicle traits significantly influence grain yield, making them a primary target for rice phenotyping studies. However, most existing techniques are limited to controlled…