What is it about?

Evaluating rice seed germination is vital for farmers. We categorized seedlings into two types: single and clustered. Using a UAV-mounted camera, we captured field images and applied the U-Net model to detect, classify, and count the seedlings accurately.

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Perspectives

I hope this article provides readers with a general understanding of the growth process of rice, a crop consumed by 50% of the world’s population. I also hope that research in precision agriculture, especially in rice fields, can support farmers—people who often face many hardships both in their work and daily lives.

Trong Hieu Luu
Can Tho University

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This page is a summary of: Design a Computer Vision Approach to Localize, Detect and Count Rice Seedlings Captured by a UAV-Mounted Camera, Computers Materials & Continua, January 2025, Tsinghua University Press,
DOI: 10.32604/cmc.2025.064007.
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