Cotton Weed-YOLO: A Lightweight and Highly Accurate Cotton Weed Identification Model for Precision Agriculture
Precise weed recognition is an important step towards achieving intelligent agriculture. In this paper, a novel weed recognition model, Cotton Weed-YOLO, is proposed to improve the accuracy and efficiency of weed detection. CW-YOLO is based on YOLOv8 and introduces a dual-branch structure combining...
Saved in:
| Main Authors: | Jinghuan Hu, He Gong, Shijun Li, Ye Mu, Ying Guo, Yu Sun, Tianli Hu, Yu Bao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/14/12/2911 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Weed Management in Cotton
by: J. A. Ferrell, et al.
Published: (2020-05-01) -
Weed Management in Cotton
by: J. A. Ferrell, et al.
Published: (2020-05-01) -
A lightweight weed detection model for cotton fields based on an improved YOLOv8n
by: Jun Wang, et al.
Published: (2025-01-01) -
A Lightweight Cotton Field Weed Detection Model Enhanced with EfficientNet and Attention Mechanisms
by: Lu Zheng, et al.
Published: (2024-11-01) -
A customized convolutional neural network-based approach for weeds identification in cotton crops
by: Hafiz Muhammad Faisal, et al.
Published: (2025-01-01)