GE-YOLO for Weed Detection in Rice Paddy Fields
Weeds are a significant adverse factor affecting rice growth, and their efficient removal necessitates an accurate, efficient, and well-generalizing weed detection method. However, weed detection faces challenges such as a complex vegetation environment, the similar morphology and color of weeds, an...
Saved in:
| Main Authors: | Zimeng Chen, Baifan Chen, Yi Huang, Zeshun Zhou |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/5/2823 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fusion of multi-scale attention for aerial images small-target detection model based on PARE-YOLO
by: Huiying Zhang, et al.
Published: (2025-02-01) -
Cotton Weed-YOLO: A Lightweight and Highly Accurate Cotton Weed Identification Model for Precision Agriculture
by: Jinghuan Hu, et al.
Published: (2024-12-01) -
AHG-YOLO: multi-category detection for occluded pear fruits in complex orchard scenes
by: Na Ma, et al.
Published: (2025-05-01) -
Multiclass weed and crop detection using optimized YOLO models on edge devices
by: Arjun Upadhyay, et al.
Published: (2025-08-01) -
Research on Fire Smoke Detection Algorithm Based on Improved YOLOv8
by: Tianxin Zhang, et al.
Published: (2024-01-01)