An Intelligent Field Monitoring System Based on Enhanced YOLO-RMD Architecture for Real-Time Rice Pest Detection and Management
This study presents a comprehensive solution for precise and timely pest monitoring in field environments through the development of an advanced rice pest detection system based on the YOLO-RMD model. Addressing critical challenges in real-time detection accuracy and environmental adaptability, the...
Saved in:
| Main Authors: | Jiangdong Yin, Jun Zhu, Gang Chen, Lihua Jiang, Huanhuan Zhan, Haidong Deng, Yongbing Long, Yubin Lan, Binfang Wu, Haitao Xu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
|
| Series: | Agriculture |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2077-0472/15/8/798 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Towards Precise Papaya Ripeness Assessment: A Deep Learning Framework with Dynamic Detection Heads
by: Haohai You, et al.
Published: (2025-07-01) -
Sec-CLOCs: Multimodal Back-End Fusion-Based Object Detection Algorithm in Snowy Scenes
by: Rui Gong, et al.
Published: (2024-11-01) -
Autonomous Aerial Vehicle Object Detection Based on Spatial Perception and Multiscale Semantic and Detail Feature Fusion
by: Wei Rao, et al.
Published: (2025-01-01) -
A High-Precision Defect Detection Approach Based on BiFDRep-YOLOv8n for Small Target Defects in Photovoltaic Modules
by: Yi Lu, et al.
Published: (2025-04-01) -
Rice Canopy Disease and Pest Identification Based on Improved YOLOv5 and UAV Images
by: Gaoyuan Zhao, et al.
Published: (2025-06-01)