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Paper Citation Record · LEDGER

Underwater Image Enhancement with Cascaded Contrastive Learning

As of 13 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 0 inbound Pith citation observations for arXiv:2411.10682.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.10682 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:31:21.310528Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

56 of 56 outbound references displayed

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  • verified fuzzy38
  • unresolved17
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9ebbfe15-4fb1-4c24-bc99-eb354496c8a0 · outbound

This paper cites Applications of geo-referenced underwater photo mosaics in marine biology and archaeology,.

Underwater Image Enhancement with Cascaded Contrastive Learning Applications of geo-referenced underwater photo mosaics in marine biology and archaeology,

Reference 1

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Observation 1f25ad7d-ad13-4a01-9967-15b9daf77f3f · outbound

This paper cites Detecting marine organisms via joint attention-relation learning for marine video surveillance,.

Underwater Image Enhancement with Cascaded Contrastive Learning Detecting marine organisms via joint attention-relation learning for marine video surveillance,

Reference 2

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Observation e0150a85-0a3a-4dd6-b49f-aaea4dd5260b · outbound

This paper cites Bidirectional collaborative mentoring network for marine organism detection and be- yond,.

Underwater Image Enhancement with Cascaded Contrastive Learning Bidirectional collaborative mentoring network for marine organism detection and be- yond,

Reference 3

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Observation f0dabbb9-f964-4652-8c2a-3198da9225bf · outbound

This paper cites Inverse synthetic aperture sonar imaging of underwater vehicles utilizing 3-d rotations,.

Underwater Image Enhancement with Cascaded Contrastive Learning Inverse synthetic aperture sonar imaging of underwater vehicles utilizing 3-d rotations,

Reference 4

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Observation bf957c44-3b32-4f4a-b6d9-cb0f9ab33b53 · outbound

This paper cites An optical image transmission system for deep sea creature sampling mis- sions using autonomous underwater vehicle,.

Underwater Image Enhancement with Cascaded Contrastive Learning An optical image transmission system for deep sea creature sampling mis- sions using autonomous underwater vehicle,

Reference 5

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Observation 5b1abdce-ff82-4434-a0f2-2d09cd1ae7c8 · outbound

This paper cites Decoupled variational retinex for reconstruction and fusion of underwater shallow depth-of-field image with parallax and moving objects,.

Underwater Image Enhancement with Cascaded Contrastive Learning Decoupled variational retinex for reconstruction and fusion of underwater shallow depth-of-field image with parallax and moving objects,

Reference 6

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Observation 58ffdb8a-8731-4034-a581-5bd18d7ff116 · outbound

This paper cites Single image super-resolution quality assessment: a real-world dataset, subjective studies, and an objective metric,.

Underwater Image Enhancement with Cascaded Contrastive Learning Single image super-resolution quality assessment: a real-world dataset, subjective studies, and an objective metric,

Reference 7

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Observation a53bef4a-6f74-4025-b1d1-4e57a1152e39 · outbound

This paper cites Perception-and- cognition-inspired quality assessment for sonar image super-resolution,.

Underwater Image Enhancement with Cascaded Contrastive Learning Perception-and- cognition-inspired quality assessment for sonar image super-resolution,

Reference 8

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Source-reported events for the cited work

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Observation 9d35a024-bce3-4884-accf-2fe92b2b134e · outbound

This paper cites Underwater optical imaging: the past, the present, and the prospects,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater optical imaging: the past, the present, and the prospects,

Reference 9

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Observation 13a4e50f-1061-442b-8ce1-bf3440613cfc · outbound

This paper cites Underwater camera: Improving visual perception via adaptive dark pixel prior and color correction,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater camera: Improving visual perception via adaptive dark pixel prior and color correction,

Reference 10

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Observation 19b14902-ae5a-4996-b00c-2ae5d134ef75 · outbound

This paper cites Underwater image enhancement quality evaluation: Benchmark dataset and objective met- ric,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater image enhancement quality evaluation: Benchmark dataset and objective met- ric,

Reference 11

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Observation c80ac4d7-0112-4841-b338-4d7144053f48 · outbound

This paper cites Underwater image en- hancement with hyper-laplacian reflectance priors,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater image en- hancement with hyper-laplacian reflectance priors,

Reference 12

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Observation fc3dda7a-15ed-4d87-82ef-f961ffe8a465 · outbound

This paper cites Reference- free quality assessment of sonar images via contour degradation mea- surement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Reference- free quality assessment of sonar images via contour degradation mea- surement,

Reference 13

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Observation 324a02b4-bd91-4e21-bacb-57aac09ae3ea · outbound

This paper cites No-reference quality assessment of underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning No-reference quality assessment of underwater image enhancement,

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 836af2be-37a1-49a4-b355-87ade1b72f32 · outbound

This paper cites Un- supervised decomposition and correction network for low-light image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Un- supervised decomposition and correction network for low-light image enhancement,

Reference 15

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Observation 129ec888-ed82-4874-809d-f5d3682c4783 · outbound

This paper cites DTKD- Net: Dual-teacher knowledge distillation lightweight network for water- related optics image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning DTKD- Net: Dual-teacher knowledge distillation lightweight network for water- related optics image enhancement,

Reference 16

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Observation 0d230b51-efe5-450a-afd6-b18cbe0643af · outbound

This paper cites Underwater image enhancement with lightweight cascaded network,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater image enhancement with lightweight cascaded network,

Reference 17

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Observation fa03fc7c-e3a2-466c-a5db-e9b0b5ad28ea · outbound

This paper cites Perception-driven deep underwater image enhancement without paired supervision,.

Underwater Image Enhancement with Cascaded Contrastive Learning Perception-driven deep underwater image enhancement without paired supervision,

Reference 18

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Source-reported events for the cited work

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Observation 030fe0ff-d7b5-4735-b3d7-a325f9f9e210 · outbound

This paper cites Underwater scene prior inspired deep underwater image and video enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater scene prior inspired deep underwater image and video enhancement,

Reference 19

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Observation 3666ded2-c17f-4a30-800f-bbb919b31379 · outbound

This paper cites An underwater image enhancement benchmark dataset and beyond,.

Underwater Image Enhancement with Cascaded Contrastive Learning An underwater image enhancement benchmark dataset and beyond,

Reference 20

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Observation ec126d94-ea3a-4004-93ce-e51ec10497eb · outbound

This paper cites Underwater image enhancement via medium transmission-guided multi-color space embedding,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater image enhancement via medium transmission-guided multi-color space embedding,

Reference 21

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Observation 57248962-cdcc-4102-9ab1-906012ab20da · outbound

This paper cites HCLR-Net: Hybrid contrastive learning regularization with locally randomized perturbation for underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning HCLR-Net: Hybrid contrastive learning regularization with locally randomized perturbation for underwater image enhancement,

Reference 22

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Observation bbadb182-c559-4fef-80bc-7e6233bef85f · outbound

This paper cites Dual-path joint correction network for underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Dual-path joint correction network for underwater image enhancement,

Reference 23

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Observation 542afc83-e250-402a-8018-900446a30abb · outbound

This paper cites Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement.

Underwater Image Enhancement with Cascaded Contrastive Learning Five A$^{+}$ Network: You Only Need 9K Parameters for Underwater Image Enhancement

Reference 24

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Observation 5899a2a9-0ea0-420d-a6df-f423a7af5a81 · outbound

This paper cites Two-branch deep neural network for underwater image enhancement in HSV color space,.

Underwater Image Enhancement with Cascaded Contrastive Learning Two-branch deep neural network for underwater image enhancement in HSV color space,

Reference 25

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Observation 13f6f62c-7ced-469d-84f1-7a8cb51ed070 · outbound

This paper cites SGUIE-Net: Semantic attention guided underwater image enhancement with multi- scale perception,.

Underwater Image Enhancement with Cascaded Contrastive Learning SGUIE-Net: Semantic attention guided underwater image enhancement with multi- scale perception,

Reference 26

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Source-reported events for the cited work

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Observation bd9a6dac-e9fc-406b-a753-e986f4a49cff · outbound

This paper cites Semantic-aware texture-structure feature collaboration for underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Semantic-aware texture-structure feature collaboration for underwater image enhancement,

Reference 27

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Source-reported events for the cited work

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Observation 937e4cf2-9580-44aa-bf65-67c6f741d4a5 · outbound

This paper cites A two-stage underwater enhancement network based on structure decom- position and characteristics of underwater imaging,.

Underwater Image Enhancement with Cascaded Contrastive Learning A two-stage underwater enhancement network based on structure decom- position and characteristics of underwater imaging,

Reference 28

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Source-reported events for the cited work

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Observation 61e5356c-a17b-48b3-8734-a9f6668623c6 · outbound

This paper cites Contrastive learning for compact single image dehazing,.

Underwater Image Enhancement with Cascaded Contrastive Learning Contrastive learning for compact single image dehazing,

Reference 29

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Observation a78caa67-7aaf-4898-99b4-5378f2089806 · outbound

This paper cites ImageNet classification with deep convolutional neural networks,.

Underwater Image Enhancement with Cascaded Contrastive Learning ImageNet classification with deep convolutional neural networks,

Reference 30

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Source-reported events for the cited work

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Observation 1a303b42-ccfd-426b-821c-597b4dc0ea27 · outbound

This paper cites ImageNet: A large-scale hierarchical image database,.

Underwater Image Enhancement with Cascaded Contrastive Learning ImageNet: A large-scale hierarchical image database,

Reference 31

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Source-reported events for the cited work

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Observation e793b857-3e08-480f-8d53-056f4ed0c803 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Underwater Image Enhancement with Cascaded Contrastive Learning Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 32

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Observation d1ebd6a1-490e-4ebf-b447-d99f3104c9bf · outbound

This paper cites Deep residual learning for image recognition,.

Underwater Image Enhancement with Cascaded Contrastive Learning Deep residual learning for image recognition,

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation dabc5f7f-d8b5-4bb0-b70a-cd7a18e28e61 · outbound

This paper cites Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connec- tions,.

Underwater Image Enhancement with Cascaded Contrastive Learning Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connec- tions,

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 4cd7e9f6-9a5a-4f07-9cdf-9c4ddc656d8d · outbound

This paper cites A deep CNN method for un- derwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning A deep CNN method for un- derwater image enhancement,

Reference 35

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raw_fallback, observed 2026-08-12T19:31:21.489523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.264302Z digest=sha256:9d5fcb967530ef56768b3b1b0b5583c56c5ccb687a20c9cd2750580c39017852

Observation 67bbe465-2a08-4bad-bdb7-1d044d5edf10 · outbound

This paper cites Uncertainty inspired underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Uncertainty inspired underwater image enhancement,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.266526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.266526Z digest=sha256:c910b5ccdffc81ec6d04f040edb26bd364509c564c531e0c0ebaace0aa1783e4

Observation 4b38a362-7ca0-41af-8549-02767ba20a11 · outbound

This paper cites Underwater ranker: Learn which is better and how to be better,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater ranker: Learn which is better and how to be better,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.477288Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.268734Z digest=sha256:ddeb15a7958c6e78ef9204b2b3b40ab2b1a9c36fba58c0cd1b6608d787fee4a5

Observation 72d72258-ed5a-47f6-b43b-d0f290b5db45 · outbound

This paper cites Data-efficient image recognition with contrastive predictive coding,.

Underwater Image Enhancement with Cascaded Contrastive Learning Data-efficient image recognition with contrastive predictive coding,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.469547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.271019Z digest=sha256:cbcccabba2849f86453c37f2d8a5008eead52ce6522120ce097a1bdac71bf27a

Observation 86ad3c9b-c1b0-425f-8510-e451b58f42ea · outbound

This paper cites Contrastive multiview coding,.

Underwater Image Enhancement with Cascaded Contrastive Learning Contrastive multiview coding,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.462175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.273166Z digest=sha256:5953983e2f4632aba249f5b7d41408dc3167126822dcfc5d66af17deb38b697d

Observation f839c314-a7cf-427a-b237-907ec1f03a02 · outbound

This paper cites Time-contrastive networks: Self-supervised learning from video,.

Underwater Image Enhancement with Cascaded Contrastive Learning Time-contrastive networks: Self-supervised learning from video,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.455297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.275148Z digest=sha256:61bdeed1260bca2aa481b7cedbb133b0266b66483cbb2ce266caf34c2ec384c4

Observation cd4614a5-9c70-4063-9b0d-6b922f20edc6 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

Underwater Image Enhancement with Cascaded Contrastive Learning A simple framework for contrastive learning of visual representations,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.448170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.277376Z digest=sha256:1ba66cae17064ae2619f844c1b89f505b32c134b4bed34ce847f0b827c2b793f

Observation 991fe70c-1634-4526-9f3f-775ae477a76a · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

Underwater Image Enhancement with Cascaded Contrastive Learning Momentum contrast for unsupervised visual representation learning,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.440524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.279684Z digest=sha256:b52de790cb519854116042650ff7fa1a735b6543c8f2c39694a24fcafce709bf

Observation 82d23835-0e25-4ae7-a4e5-b8e35b34ad4c · outbound

This paper cites UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning.

Underwater Image Enhancement with Cascaded Contrastive Learning UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-12T19:31:21.336551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.281904Z digest=sha256:e1d1a37f7f6790386c6c7c85bcd973325544b0b2b7eccababd9c3898b32255ba

Observation 6e95e23e-573d-4baa-92d5-7428fa0d43b5 · outbound

This paper cites Twin adversarial contrastive learning for underwater image enhancement and beyond,.

Underwater Image Enhancement with Cascaded Contrastive Learning Twin adversarial contrastive learning for underwater image enhancement and beyond,

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.284597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.284597Z digest=sha256:864ceb8994446a3368dda04e96558e8d46243506b62593daa03b7a1f804b864d

Observation d422e7e9-1221-4181-b907-056432d20f1d · outbound

This paper cites FFA-Net: Feature fusion attention network for single image dehazing,.

Underwater Image Enhancement with Cascaded Contrastive Learning FFA-Net: Feature fusion attention network for single image dehazing,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.427916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.287067Z digest=sha256:9f77627444f36cc23df4da508fdfd5da2b058f36681cf081ba1b920d75b4cbf8

Observation f3a1f534-d7fd-45f2-b15c-89bc4c72d062 · outbound

This paper cites Learning enriched features for fast image restoration and enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Learning enriched features for fast image restoration and enhancement,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.419787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.289300Z digest=sha256:812614f0f4b22d594d29730e8d728ce4af9a15b1af75aae365c9de1fda95da1c

Observation 6b226410-2b77-4f46-a16b-2673e1d74a1c · outbound

This paper cites Image quality assessment: from error visibility to structural similarity,.

Underwater Image Enhancement with Cascaded Contrastive Learning Image quality assessment: from error visibility to structural similarity,

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.291517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.291517Z digest=sha256:923f0588d9cd3f899e9eb5741b737e8d25da36264f249397151bf29ce58393e9

Observation 18c70858-14fd-4129-a1eb-d21cb740b95a · outbound

This paper cites Fast underwater image enhancement for improved visual perception,.

Underwater Image Enhancement with Cascaded Contrastive Learning Fast underwater image enhancement for improved visual perception,

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.293847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.293847Z digest=sha256:be6a04ee79f7e7365eb88015b3c7874883f257eee85f1753f36fa3275403d3ca

Observation 05b41f1a-42b3-484d-9b55-1f9c1e683290 · outbound

This paper cites Underwater single image color restoration using haze-lines and a new quantitative dataset,.

Underwater Image Enhancement with Cascaded Contrastive Learning Underwater single image color restoration using haze-lines and a new quantitative dataset,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.402767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.296141Z digest=sha256:04b49935ab8994c379671a314cf26cdbdc5f6f4d66b871915d8516cfda664dae

Observation 83fcb2ee-e13f-4a0b-abf5-78ba2806603f · outbound

This paper cites Real-world underwater enhancement: Challenges, benchmarks, and solutions under natural light,.

Underwater Image Enhancement with Cascaded Contrastive Learning Real-world underwater enhancement: Challenges, benchmarks, and solutions under natural light,

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.298302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.298302Z digest=sha256:72a2d4d8322f3885b8e5b97d66673e803a36391992cfdd1bbeb34575ef4838ae

Observation b4fcce42-ee34-4dcb-a519-fcb8fd0d3a8c · outbound

This paper cites Color balance and fusion for underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Color balance and fusion for underwater image enhancement,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.390404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.300365Z digest=sha256:9376314a768c9225835ffd08939ec6da378330c548aad514b63d00c02067da1a

Observation 2969473d-5d14-45f5-9146-bca11d20c76e · outbound

This paper cites Enhancement of underwater images with statistical model of background light and optimization of transmission map,.

Underwater Image Enhancement with Cascaded Contrastive Learning Enhancement of underwater images with statistical model of background light and optimization of transmission map,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.382791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.302386Z digest=sha256:f40696e523933be74133da2655c18dd68dcd9a0e5873c8dee41fe627b49ace1e

Observation 4f0c65e4-67fb-4d5f-a087-485651612faa · outbound

This paper cites Under- water image enhancement via minimal color loss and locally adaptive contrast enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning Under- water image enhancement via minimal color loss and locally adaptive contrast enhancement,

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.304504Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.304504Z digest=sha256:43ee303df7d5b99fd71af2d14ff620d6c2b625b98d324d5928881ede0c27ce99

Observation c0164097-5b6c-4b07-b8b9-7d7646295fbf · outbound

This paper cites Human-visual-system-inspired underwater image quality measures,.

Underwater Image Enhancement with Cascaded Contrastive Learning Human-visual-system-inspired underwater image quality measures,

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.306472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.306472Z digest=sha256:15135e32b09d4c3d91ed73c8b2d1f0b7f1fef62cbe9a6f04fb0eb44f1ff0b06c

Observation a3a9278f-ed58-4a05-80b3-a5377d12f3e9 · outbound

This paper cites An underwater color image quality evaluation metric,.

Underwater Image Enhancement with Cascaded Contrastive Learning An underwater color image quality evaluation metric,

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-12T19:31:21.308472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:31:21.308472Z digest=sha256:88b8c7ae7b31fa22eaff1850cfa9baf060c940a775a16c5cfe62fa18d762954b

Observation e9f1884d-758c-40a9-8b88-7c44194dc080 · outbound

This paper cites A perception- aware decomposition and fusion framework for underwater image enhancement,.

Underwater Image Enhancement with Cascaded Contrastive Learning A perception- aware decomposition and fusion framework for underwater image enhancement,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T19:31:21.360797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T19:31:21.310528Z digest=sha256:4670f442115a701c5b36b5d03583aa463c6588c2d035381cf0acaffdb3b3dd60

Pith citing papers

No inbound Pith citation observations are available.