The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
YOLO-Tomato: A Robust Algorithm for Tomato Detection Based on YOLOv3
Open accessAbstract
Automatic fruit detection is a very important benefit of harvesting robots. However, complicated environment conditions, such as illumination variation, branch, and leaf occlusion as well as tomato overlap, have made fruit detection very challenging. In this study, an improved tomato detection model called YOLO-Tomato is proposed for dealing with these problems, based on YOLOv3. A dense architecture is incorporated into YOLOv3 to facilitate the reuse of features and help to learn a more compact and accurate model. Moreover, the model replaces the traditional rectangular bounding box (R-Bbox) with a circular bounding box (C-Bbox) for tomato localization. The new bounding boxes can then match the tomatoes more precisely, and thus improve the Intersection-over-Union (IoU) calculation for the Non-Maximum Suppression (NMS). They also reduce prediction coordinates. An ablation study demonstrated the efficacy of these modifications. The YOLO-Tomato was compared to several state-of-the-art detection methods and it had the best detection performance.
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Cites
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Cited by
A detection algorithm for cherry fruits based on the improved YOLO-v4 model
Gai, R., Chen, N., & Yuan, H. (2023) · Neural Computing and Applications · doi:10.1007/s00521-021-06029-z · Cited by 388
A Lightweight YOLOv8 Tomato Detection Algorithm Combining Feature Enhancement and Attention
Yang, G., Wang, J., Nie, Z., Yang, H., & Yu, S. (2023) · Agronomy · doi:10.3390/agronomy13071824 · Cited by 323
Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion
Hasan, R. I., Yusuf, S. M., & Alzubaidi, L. (2020) · Plants · doi:10.3390/plants9101302 · Cited by 213
Improved YOLO-V3 with DenseNet for Multi-Scale Remote Sensing Target Detection
Xu, D., & Wu, Y. (2020) · Sensors · doi:10.3390/s20154276 · Cited by 141
“Reference [51] adopted circular ground truth to realize tomato detection.”
MethodFace mask detection in COVID-19: a strategic review
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Metadata
- Authors
- Liu, G., Nouaze, J. C., Touko Mbouembe, P. L., & Kim, J. H.
- Venue
- Sensors
- Publisher
- MDPI AG
- Published
- 2020-04-10
- Volume
- 20
- Issue
- 7
- Pages
- 2145
- ISSN
- 1424-8220 (ISSN-L)
- OpenAlex
- W3015736093
- Cited by
- 417
- References
- 32
- FWCI
- 34.59
- Type
- journal article
- Language
- en
- Open access
- gold
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