Semantic Segmentation of Weed and Crop with Partially Annotated Data for Automated Agriculture
Author:
Affiliation:
1. Linköping University
2. Chalmers University of Technology
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10262401/10262415/10262692.pdf?arnumber=10262692
Reference27 articles.
1. Real-Time Semantic Segmentation of Crop and Weed for Precision Agriculture Robots Leveraging Background Knowledge in CNNs
2. A DNN-based semantic segmentation for detecting weed and crop
3. Data augmentation for deep learning based semantic segmentation and crop-weed classification in agricultural robotics
4. Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture
5. A modified U-Net with a specific data argumentation method for semantic segmentation of weed images in the field
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