The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Fruit detection and positioning technology for a Camellia oleifera C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., et al. (2015) · International Journal of Computer Vision · doi:10.1007/s11263-015-0816-y · Cited by 39,380
A flexible new technique for camera calibration
Zhang, Z. (2000) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.888718 · Cited by 15,004
Advances in Neural Information Processing Systems 25
Zhang, Y., Sutton, C. A., Storkey, A., & Zoubin Ghahramani, A. (2012) · Cited by 12,653
Self-citation2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
(2015) · doi:10.1109/cvpr31182.2015 · Cited by 3,737
Deeper Insights Into Graph Convolutional Networks for Semi-Supervised Learning
Li, Q., Han, Z., & Wu, X.-M. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v32i1.11604 · Cited by 2,872
Apple detection during different growth stages in orchards using the improved YOLO-V3 model
Tian, Y., Yang, G., Wang, Z., Wang, H., Li, E., & Liang, Z. (2019) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.01.012 · Cited by 1,043
Self-citationFruit detection for strawberry harvesting robot in non-structural environment based on Mask-RCNN
Yu, Y., Zhang, K., Yang, L., & Zhang, D. (2019) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2019.06.001 · Cited by 630
Recognition and Localization Methods for Vision-Based Fruit Picking Robots: A Review
Tang, Y., Chen, M., Wang, C., Luo, L., Li, J., Lian, G., & Zou, X. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.00510 · Cited by 575
Self-citationKoirala, A., Walsh, K. B., Wang, Z., & McCarthy, C. (2019) · Precision Agriculture · doi:10.1007/s11119-019-09642-0 · Cited by 459
Faster R-CNN for multi-class fruit detection using a robotic vision system
Wan, S., & Goudos, S. (2020) · Computer Networks · doi:10.1016/j.comnet.2019.107036 · Cited by 449
Metadata
- Authors
- Tang, Y., Zhou, H., Wang, H., & Zhang, Y.
- Venue
- Expert Systems with Applications
- Publisher
- Elsevier BV
- Published
- 2023-01
- Volume
- 211
- Pages
- 118573
- ISSN
- 0957-4174 (ISSN-L)
- OpenAlex
- W4293581688
- Cited by
- 258
- References
- 33
- FWCI
- 27.77
- Type
- journal article
- Language
- en
- Open access
- closed
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.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Fruit detection and positioning technology for a Camellia oleifera C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision. https://app.cochat.ai/papers/10.1016/j.eswa.2022.118573
- The paper
- Tang, Y., Zhou, H., Wang, H., & Zhang, Y. (2023). Fruit detection and positioning technology for a Camellia oleifera C. Abel orchard based on improved YOLOv4-tiny model and binocular stereo vision. Expert Systems with Applications. https://doi.org/10.1016/j.eswa.2022.118573
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
