A Robust Tomato Counting Framework for Greenhouse Inspection Robots Using YOLOv8 and Inter-Frame Prediction
Accurate tomato yield estimation and ripeness monitoring are critical for optimizing greenhouse management. While manual counting remains labor-intensive and error-prone, this study introduces a novel vision-based framework for automated tomato counting in standardized greenhouse environments. The p...
Saved in:
| Main Authors: | Wanli Zheng, Guanglin Dai, Miao Hu, Pengbo Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
|
| Series: | Agronomy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4395/15/5/1135 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ta-YOLO: overcoming target blocked challenges in greenhouse tomato detection and counting
by: Yun Zhao, et al.
Published: (2025-07-01) -
Tomato Yield Estimation Using an Improved Lightweight YOLO11n Network and an Optimized Region Tracking-Counting Method
by: Aichen Wang, et al.
Published: (2025-06-01) -
Efficient Packaging Line Object Counting by Cross-Frame Association With Wavelet Convolutions and Trajectory Compensation
by: Longxuan Wei, et al.
Published: (2025-01-01) -
Enhanced YOLOv8 for Robust Pig Detection and Counting in Complex Agricultural Environments
by: Jian Li, et al.
Published: (2025-07-01) -
Traffic Impact Assessment System using Yolov5 and ByteTrack
by: Jin Jie Ng, et al.
Published: (2023-09-01)