Deep-CNN based Robotic Multi-Class Under-Canopy Weed Control in Precision Farming
Author:
Affiliation:
1. University of California, Los Angeles,Department of Mechanical & Aerospace Engineering,Los Angeles,CA,90095
Funder
NSF
National Institute of Food and Agriculture
USDA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09812240.pdf?arnumber=9812240
Reference26 articles.
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1. A Novel Approach to Weed Detection Using Segmentation and Image Processing Techniques;2023 World Conference on Communication & Computing (WCONF);2023-07-14
2. Neural-Kalman GNSS/INS Navigation for Precision Agriculture;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29
3. Neutral weed communities: the intersection between crop productivity, biodiversity, and weed ecosystem services;Weed Science;2023-05-11
4. YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems;Computers and Electronics in Agriculture;2023-02
5. Review on Automatic Variable-Rate Spraying Systems Based on Orchard Canopy Characterization;Informatics and Automation;2023-01-27
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