Underwater vision enhancement technologies: a comprehensive review, challenges, and recent trends
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?
The same data augmentation techniques were applied across all models, with additional preprocessing for noisy images.
“The same data augmentation techniques were applied across all models, with additional preprocessing for noisy images [18, 19].”
From Optimizing Neural Network Architecture for Medical Image Segmentation Using Monte Carlo Tree Search (2026) · cites this paper as [18]
Cites
Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A. C., Sheikh, H. R., & Simoncelli, E. P. (2004) · IEEE Transactions on Image Processing · doi:10.1109/tip.2003.819861 · Cited by 57,892 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Optimizing Neural Network Architecture for Medical Image Segmentation Using Monte Carlo Tree Search
Meng, L., Nie, F., Zhang, Y., & Han, C. (2026) · arXiv · doi:10.48550/arxiv.2602.22361
“The same data augmentation techniques were applied across all models, with additional preprocessing for noisy images [18, 19].”
- Authors
- Zhou, J., Yang, T., & Zhang, W.
- Affiliations
- Dalian Maritime University (CN)
- Corresponding author
- Zhou, Jingchun
- Zhang, Weishi
- Venue
- Applied Intelligence
- Published
- 2022-06-01
- Volume
- 53
- Issue
- 3
- Pages
- 3594-3621
- ISSN
- 0924-669X (ISSN-L)
- 1573-7497
- OpenAlex
- W4281937845
- Cited by
- 149
- References
- 1
- Citations by year
- 2026: 32 · 2025: 49 · 2024: 43 · 2023: 21 · 2022: 4
- FWCI
- 9.57
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Applied Intelligence (publishedVersion)
- Funders
- National Natural Science Foundation of China (61702074)
- Liaoning Provincial Natural Science Foundation of China (20170520196)
- Fundamental Research Funds for the Central Universities (3132019205 and 3132019354)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Enhancement Techniques
- Physical Sciences › Engineering › Ocean Engineering › Underwater Vehicles and Communication Systems
- Physical Sciences › Engineering › Media Technology › Image Processing Techniques and Applications
- Keywords
- underwater image enhancement, underwater image degradation, underwater image dataset, underwater object detection
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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