YOLOWeeds: A novel benchmark of YOLO object detectors for multi-class weed detection in cotton production systems
Integrity signals
Registry
Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In precision farming, herbicides can be applied selectively to target weeds without affecting crops.
“In precision farming, herbicides can be applied selectively to target weeds without affecting crops [105,106].”
From The YOLO Framework: A Comprehensive Review of Evolution, Applications, and Benchmarks in Object Detection (2024) · cites this paper as [106]
Cites
You Only Look Once: Unified, Real-Time Object Detection
Redmon, J., Divvala, S., Girshick, R., & Farhadi, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.91 · Cited by 53,803 · see citing works
The Pascal Visual Object Classes Challenge: A Retrospective
Everingham, M., Eslami, S. M. A., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-014-0733-5 · Cited by 7,139 · see citing works
Deep Learning for Generic Object Detection: A Survey
Liu, L., Ouyang, W., Wang, X., Fieguth, P., Chen, J., Liu, X., & Pietikäinen, M. (2020) · International Journal of Computer Vision · doi:10.1007/s11263-019-01247-4 · Cited by 2,965 · see citing works
Bag of Tricks for Image Classification with Convolutional Neural Networks
He, T., Zhang, Z., Zhang, H., Zhang, Z., Xie, J., & Li, M. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2019.00065 · Cited by 1,680 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Badgujar, C. M., Poulose, A., & Gan, H. (2024) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2024.109090 · Cited by 411 · see citing works
Ali, M. L., & Zhang, Z. (2024) · Computers · doi:10.3390/computers13120336 · Cited by 383 · see citing works
- Authors
- Dang, F., Chen, D., Lu, Y., & Li, Z.
- Affiliations
- Michigan State University (US)
- Corresponding author
- Lu, Yuzhen
- Venue
- Computers and Electronics in Agriculture
- Publisher
- Elsevier BV
- Published
- 2023-02
- Volume
- 205
- Pages
- 107655
- ISSN
- 0168-1699 (ISSN-L)
- OpenAlex
- W4317513060
- Cited by
- 313
- References
- 4
- Citations by year
- 2026: 85 · 2025: 112 · 2024: 86 · 2023: 30
- FWCI
- 49.32
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Computers and Electronics in Agriculture (publishedVersion)
- Funders
- Cotton Incorporated (21-005)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Smart Agriculture and AI
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Life Sciences › Agricultural and Biological Sciences › Plant Science › Weed Control and Herbicide Applications
- Keywords
- weed detection, cotton production, benchmarking, herbicide resistance, weed control, YOLOv5, YOLOv4, data augmentation, Monte Carlo cross-validation, multi-class object detection, real-time detection, weed growth stage
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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