CWRepViT-Net: An encoder-decoder deep learning framework with RepViT blocks for crop weed semantic segmentation in soybean fields through their life journey

With the world's population growing at a steady rate, demand for agricultural products continues to increase. To meet this expanding need, it is critical to employ cutting-edge knowledge and technologies. Remote sensing data in conjunction with computer vision algorithms, plays an emerging and...

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Bibliographic Details

Published in:	Smart Agricultural Technology
Main Authors:	Masoomeh Gomroki, Dilshan Benaragama, Christopher James Henry, Nasem Badreldin, Robert Gulden
Format:	Article
Language:	English
Published:	Elsevier 2025-12-01
Subjects:	Crop and weed semantic segmentation Soybean Encoder-decoder architecture RepViT Precision agriculture
Online Access:	http://www.sciencedirect.com/science/article/pii/S2772375525007038