The DOI matches its Crossref record; 58 of the 58 references it cites were found in a registry or an index.
Boosting R-CNN: Reweighting R-CNN samples by RPN’s error for underwater object detection
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Cites
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Ren, S., He, K., Girshick, R., & Sun, J. (2017) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2016.2577031 · Cited by 73,472
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
Microsoft COCO: Common Objects in Context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., & Zitnick, C. L. (2014) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-10602-1_48 · Cited by 45,460
Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation
Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684
(2016) · Cited by 31,590
Focal Loss for Dense Object Detection
Lin, T.-Y., Goyal, P., Girshick, R., He, K., & Dollar, P. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.324 · Cited by 30,581
SSD: Single Shot MultiBox Detector
Liu, W., Anguelov, D., Erhan, D., Szegedy, C., Reed, S., Fu, C.-Y., & Berg, A. C. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_2 · Cited by 22,128
YOLO9000: Better, Faster, Stronger
Redmon, J., & Farhadi, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.690 · Cited by 19,892
The pascal visual object classes (VOC) challenge
Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599
End-to-End Object Detection with Transformers
Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A., & Zagoruyko, S. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58452-8_13 · Cited by 18,285
Cited by
A systematic review and analysis of deep learning-based underwater object detection
Xu, S., Zhang, M., Song, W., Mei, H., He, Q., & Liotta, A. (2023) · Neurocomputing · doi:10.1016/j.neucom.2023.01.056 · Cited by 319
AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications
Chen, P., Wu, L., & Wang, L. (2023) · Applied Sciences · doi:10.3390/app131810258 · Cited by 155
Metadata
- Authors
- Song, P., Li, P., Dai, L., Wang, T., & Chen, Z.
- Venue
- Neurocomputing
- Publisher
- Elsevier BV
- Published
- 2023-04
- Volume
- 530
- Pages
- 150-164
- ISSN
- 0925-2312 (ISSN-L)
- OpenAlex
- W4320033720
- Cited by
- 298
- References
- 58
- FWCI
- 27.09
- Type
- journal article
- Language
- en
- Open access
- green
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- CoChat. (2026). Citation check: Boosting R-CNN: Reweighting R-CNN samples by RPN’s error for underwater object detection. https://app.cochat.ai/papers/10.1016/j.neucom.2023.01.088
- The paper
- Song, P., Li, P., Dai, L., Wang, T., & Chen, Z. (2023). Boosting R-CNN: Reweighting R-CNN samples by RPN’s error for underwater object detection. Neurocomputing. https://doi.org/10.1016/j.neucom.2023.01.088
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