An Efficient Detection of the Pitaya Growth Status Based on the YOLOv8n-CBN Model
Abstract
:1. Introduction
2. Materials and Methods
2.1. Construction of Data Sets
2.2. Methods
2.2.1. YOLOv8n Network Structure
2.2.2. CBAM Attentional Mechanisms
2.2.3. The BiFPN Network
2.2.4. The C2F_DCN Module
2.2.5. YOLOv8n-CBN Network Architecture
3. Results and Discussion
3.1. Experimental Environment
3.2. Ablation Experiment
3.3. Performance Comparison of Different Models
3.4. A Comparative Analysis of the Loss Function Prior to and following Improvement
3.5. Comparison of the Growth State of Pitaya Fruit Results before and after the Improved Model
4. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Appendix A
References
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None | CBAM | BiFPN | C2F-DCN | P | R | F1 | mAP @0.5 | mAP @0.50–0.95 | Inference Time | Weight |
---|---|---|---|---|---|---|---|---|---|---|
✓ | 0.880 | 0.805 | 0.842 | 0.890 | 0.470 | 5.6 ms | 6.2 MB | |||
✓ | 0.895 | 0.853 | 0.873 | 0.905 | 0.477 | 5.6 ms | 6.2 MB | |||
✓ | ✓ | 0.881 | 0.854 | 0.867 | 0.911 | 0.476 | 5.8 ms | 6.2 MB | ||
✓ | ✓ | 0.893 | 0.835 | 0.863 | 0.902 | 0.478 | 6.3 ms | 6.4 MB | ||
✓ | ✓ | ✓ | 0.911 | 0.843 | 0.876 | 0.911 | 0.482 | 6.4 ms | 6.4 MB |
YOLOv3-Tiny | YOLOv5s | YOLOv5m | YOLOv8n | YOLOv8n-CBN | |
---|---|---|---|---|---|
P | 0.823 | 0.859 | 0.872 | 0.880 | 0.911 |
R | 0.780 | 0.884 | 0.872 | 0.805 | 0.843 |
F1 | 0.801 | 0.871 | 0.872 | 0.842 | 0.876 |
[email protected] | 0.844 | 0.904 | 0.906 | 0.890 | 0.911 |
[email protected]–0.95 | 0.381 | 0.432 | 0.466 | 0.470 | 0.482 |
inference time | 3.9 ms | 5.7 ms | 11.6 ms | 5.6 ms | 6.4 ms |
weight | 16.9 MB | 14.1 MB | 40.8 MB | 6.2 MB | 6.4 MB |
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Share and Cite
Qiu, Z.; Zhuo, S.; Li, M.; Huang, F.; Mo, D.; Tian, X.; Tian, X. An Efficient Detection of the Pitaya Growth Status Based on the YOLOv8n-CBN Model. Horticulturae 2024, 10, 899. https://doi.org/10.3390/horticulturae10090899
Qiu Z, Zhuo S, Li M, Huang F, Mo D, Tian X, Tian X. An Efficient Detection of the Pitaya Growth Status Based on the YOLOv8n-CBN Model. Horticulturae. 2024; 10(9):899. https://doi.org/10.3390/horticulturae10090899
Chicago/Turabian StyleQiu, Zhi, Shiyue Zhuo, Mingyan Li, Fei Huang, Deyun Mo, Xuejun Tian, and Xinyuan Tian. 2024. "An Efficient Detection of the Pitaya Growth Status Based on the YOLOv8n-CBN Model" Horticulturae 10, no. 9: 899. https://doi.org/10.3390/horticulturae10090899