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Paper Citation Record · LEDGER

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges

As of 14 August 2026, this Paper Citation Record lists 100 of 181 outbound references and 1 inbound Pith citation observation for arXiv:2412.11840.

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

pith.paper-citation-record.v1
2412.11840 v1

Coverage vector

measured 100 of 181 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:34:44.284544Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:19:51.716495Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:19:52.031018Z

Reference resolution

100 of 181 outbound references displayed

  • verified exact12
  • verified fuzzy0
  • unresolved87
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  • malformed identifier1
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External citation measurements

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Outbound references

Observation 67d601ba-3675-47a6-a55a-28883136170e · outbound

This paper cites Multi-auv motion planning for archeological site mapping and photogrammetric reconstruction,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Multi-auv motion planning for archeological site mapping and photogrammetric reconstruction,

Reference 1

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Observation c3474ab6-34d5-4318-9387-e4389d8e4cff · outbound

This paper cites Auv ”tuna-sand.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Auv ”tuna-sand

Reference 2

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Observation 02ab856e-9227-47ea-92e4-a5bd244349fe · outbound

This paper cites Multi-actuated auv body for windfarm inspection: Lessons from the bio-inspired robofish field trials,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Multi-actuated auv body for windfarm inspection: Lessons from the bio-inspired robofish field trials,

Reference 3

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Observation 1817e456-5a74-4ae4-bb90-2345c2dc1266 · outbound

This paper cites The hugin 1000 autonomous underwater vehicle for military applications,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges The hugin 1000 autonomous underwater vehicle for military applications,

Reference 4

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Observation 04f44068-5c04-4e88-9331-37bf473ebe58 · outbound

This paper cites Swdd: Sonar wall detection dataset,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Swdd: Sonar wall detection dataset,

Reference 5

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Observation 16e0cb0d-ff9c-458d-9455-6358fdf8ba88 · outbound

This paper cites Data augmentation using image translation for underwater sonar image segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Data augmentation using image translation for underwater sonar image segmentation,

Reference 6

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Observation e9f8c55f-ad65-4a77-9973-c02a36a799b6 · outbound

This paper cites Recent advances in ai for navigation and control of underwater robots,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Recent advances in ai for navigation and control of underwater robots,

Reference 7

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Observation 290bc9a9-2864-44a4-8787-6a36da2f4a1f · outbound

This paper cites Autonomous object identification in mine countermeasure missions,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Autonomous object identification in mine countermeasure missions,

Reference 8

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Observation aec57c8f-8051-4f55-9c1e-142953bcaf35 · outbound

This paper cites Archaeo- logic machine learning for shipwreck detection using lidar and sonar,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Archaeo- logic machine learning for shipwreck detection using lidar and sonar,

Reference 9

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Observation f3e5fa3f-ee12-4f6e-a591-e779b72baa74 · outbound

This paper cites Lsts toolchain framework for deep learning implementation into autonomous underwater vehicle,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Lsts toolchain framework for deep learning implementation into autonomous underwater vehicle,

Reference 10

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Observation 59978f9b-d8ec-4999-ac89-e213187cc8b2 · outbound

This paper cites Mission planning and safety assessment for pipeline inspection using autonomous underwater vehicles: A framework based on behavior trees,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Mission planning and safety assessment for pipeline inspection using autonomous underwater vehicles: A framework based on behavior trees,

Reference 11

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Observation ab96d3af-4b0b-4d3e-995a-663b87dbbdcf · outbound

This paper cites A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A.I. Robustness: a Human-Centered Perspective on Technological Challenges and Opportunities

Reference 12

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Observation a533081b-c0dd-429d-b208-ce2184e40d82 · outbound

This paper cites Safe ai for cps (invited paper),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Safe ai for cps (invited paper),

Reference 13

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Observation 3c5acd0d-f2db-4f3d-8b84-34f691948c94 · outbound

This paper cites Opening the Black Box of Deep Neural Networks via Information.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Opening the Black Box of Deep Neural Networks via Information

Reference 14

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Observation e424f8e8-86df-4782-b0c0-07158a5a2528 · outbound

This paper cites Ai challenges for society and ethics,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Ai challenges for society and ethics,

Reference 15

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Observation c36954fe-e6c0-4d26-801a-03b798a2ee63 · outbound

This paper cites Explainable AI: current status and future directions.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Explainable AI: current status and future directions

Reference 16

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Observation 53acb87c-c3a8-49c3-9797-bf5d78f7a7e1 · outbound

This paper cites Rethinking explainable machines: The gdprs “right to explanation.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Rethinking explainable machines: The gdprs “right to explanation

Reference 17

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Observation 8790f3e7-975b-41cd-bd0d-5cd0f31dee2d · outbound

This paper cites Explaining Explanations: An Overview of Interpretability of Machine Learning.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Explaining Explanations: An Overview of Interpretability of Machine Learning

Reference 18

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Observation b0a2b1af-3691-4932-9920-9e5344feee8b · outbound

This paper cites An introduction to underwater acoustics: Principles and applications,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges An introduction to underwater acoustics: Principles and applications,

Reference 19

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Observation 4fe17820-5a25-40ed-8afe-61a949b1f2c1 · outbound

This paper cites A review on deep learning-based approaches for automatic sonar target recognition,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A review on deep learning-based approaches for automatic sonar target recognition,

Reference 20

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Observation df4fe637-451b-4127-8474-2aa9f839b42c · outbound

This paper cites Survey on deep learning based computer vision for sonar imagery,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Survey on deep learning based computer vision for sonar imagery,

Reference 21

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Observation b7ec1bc1-182d-4cff-8835-d4b922b8065f · outbound

This paper cites Underwater target detection using deep learning: Methodologies, challenges, applications, and future evolution,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Underwater target detection using deep learning: Methodologies, challenges, applications, and future evolution,

Reference 22

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Observation ecae6357-b815-457a-9f9e-d8d129c996c2 · outbound

This paper cites Underwater target recognition methods based on the framework of deep learning: A survey,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Underwater target recognition methods based on the framework of deep learning: A survey,

Reference 23

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Observation 6b13fe5e-e7ff-46a2-ad46-3739510fd089 · outbound

This paper cites A review on the wavelet methods for sonar image segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A review on the wavelet methods for sonar image segmentation,

Reference 24

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Observation d9996ade-2842-43f9-b1e4-e14319c5cf76 · outbound

This paper cites Acoustic fish species identification using deep learning and machine learning algorithms: A systematic review,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Acoustic fish species identification using deep learning and machine learning algorithms: A systematic review,

Reference 25

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Observation 0fccc934-e3c2-4b49-92e0-097a555bad3e · outbound

This paper cites Deep learning algorithms for sonar imagery analysis and its application in aquaculture: A review,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Deep learning algorithms for sonar imagery analysis and its application in aquaculture: A review,

Reference 26

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Observation e2169fa4-ff65-4695-87e5-88070afcc1da · outbound

This paper cites A survey of underwater acoustic data classification methods using deep learning for shoreline surveillance,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A survey of underwater acoustic data classification methods using deep learning for shoreline surveillance,

Reference 27

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Observation 67f4dc3d-1db4-413f-b2db-92c8171ad0f0 · outbound

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

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Imagenet classification with deep convolutional neural networks,

Reference 28

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Observation e2687011-a249-4c5a-85e9-1a761bc709ee · outbound

This paper cites Gradient-based learning applied to document recognition,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Gradient-based learning applied to document recognition,

Reference 29

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Observation a93da3b0-1f32-4bc1-9e94-fbaf9087a775 · outbound

This paper cites Deep residual learning for image recognition,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Deep residual learning for image recognition,

Reference 30

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Observation 4dae8f7c-2b34-4574-b866-59b4d24d61a1 · outbound

This paper cites Rich feature hierarchies for accurate object detection and semantic segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Rich feature hierarchies for accurate object detection and semantic segmentation,

Reference 31

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Observation b5d8dd92-5da4-4be0-b60b-bbf25243190e · outbound

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Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Fast r-cnn,

Reference 32

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Observation 9e97d231-e839-4e8f-882c-feb5ba056bbd · outbound

This paper cites Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Reference 33

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Observation 372d5509-7464-4888-b0c9-178cfdb73bed · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges You Only Look Once: Unified, Real-Time Object Detection

Reference 34

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Observation 5384d575-aa58-4611-8667-ee4e8821ef7b · outbound

This paper cites Ssd: Single shot multibox detector,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Ssd: Single shot multibox detector,

Reference 35

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Observation 56c981dc-45f8-4989-9644-fdd691787477 · outbound

This paper cites Attention Is All You Need.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Attention Is All You Need

Reference 36

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Observation c4303bb9-9751-46de-b9fa-0cf91683c30c · outbound

This paper cites Serial order: A parallel distributed processing approach,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Serial order: A parallel distributed processing approach,

Reference 37

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Observation 6b1b3ff1-b2b4-40d0-8add-3c61a54293ee · outbound

This paper cites Long short-term memory,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Long short-term memory,

Reference 38

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Observation ee6d7217-eb11-4621-b802-6529dc4d5249 · outbound

This paper cites End-to-End Object Detection with Transformers.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges End-to-End Object Detection with Transformers

Reference 39

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source=pdf_text observed=2026-08-11T14:34:43.996601Z digest=sha256:d08aadb00ad1ee97243ac64a24f5f639907ff16a23d418aa10f973dee24e5353

Observation 1db351aa-5f58-43ac-985f-1334f99d781c · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 40

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source=pdf_text observed=2026-08-11T14:34:44.001059Z digest=sha256:ada7008b6e5ad460dd11f8c30bda1f66165e0fa0abac70a796f79eee50efde79

Observation fde8a849-a2c0-4192-8f4c-7ed542d0f9b0 · outbound

This paper cites Rotated object detection with forward-looking sonar in underwater applications,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Rotated object detection with forward-looking sonar in underwater applications,

Reference 41

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source=pdf_text observed=2026-08-11T14:34:44.006083Z digest=sha256:3e46ff98ed76112004f893d723c6a20e8b5fe0ee70f2ca84fab4361b15bae8bb

Observation 8f9dba5e-8ca4-4c97-b57a-a2aa2442ae65 · outbound

This paper cites Real-time underwater maritime object detection in side-scan sonar images based on transformer-yolov5,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Real-time underwater maritime object detection in side-scan sonar images based on transformer-yolov5,

Reference 42

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source=pdf_text observed=2026-08-11T14:34:44.010144Z digest=sha256:86a49ce49a17cc90dfc79ca777ba48d1aba10c9e511cd7be7671fe39a5ed514f

Observation 9d5d3b9c-651f-4c3f-a985-191e44302804 · outbound

This paper cites Real-time automatic wall detection and localization based on side scan sonar images,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Real-time automatic wall detection and localization based on side scan sonar images,

Reference 43

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source=pdf_text observed=2026-08-11T14:34:44.014222Z digest=sha256:b3a3e8105e2617dc080079a9aa72a65853661deab09e458a5b9ba59313c6272d

Observation 26c5c0cb-3ae9-4aff-8b41-04d1d5f05ae4 · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges YOLOX: Exceeding YOLO Series in 2021

Reference 44

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source=pdf_text observed=2026-08-11T14:34:44.018548Z digest=sha256:0125ca43bef2686efb6446727aba3958fb84e852799357f692c30b58a9f2e7cb

Observation 0c74716d-fb6d-4abe-b666-6741cc89ee53 · outbound

This paper cites Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object Detection.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Knowledge Distillation in YOLOX-ViT for Side-Scan Sonar Object Detection

Reference 45

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source=pdf_text observed=2026-08-11T14:34:44.023660Z digest=sha256:32911f68f644c1836bbbccdd0c6001fc9fd42168a34fcfd8def898c4a5bf70c0

Observation 68736a6e-ca8d-4f6b-a7e2-f14d36a90a82 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Fully convolutional networks for semantic segmentation,

Reference 46

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source=pdf_text observed=2026-08-11T14:34:44.029042Z digest=sha256:8cf644e7cbf9404ddcf9733cadcff88188e42e13fdd06b498f7b23cbe7cb4a3d

Observation e26f3397-9a2e-4c7c-b7c9-8d063cdb48fb · outbound

This paper cites U-net: Convolutional net- works for biomedical image segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges U-net: Convolutional net- works for biomedical image segmentation,

Reference 47

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source=pdf_text observed=2026-08-11T14:34:44.033516Z digest=sha256:befda8b602f044049ec2af4b26509e50c65b504b0c197095d9c604446b103352

Observation 13c03d4d-6969-4da7-9759-6f6eb0d9fc20 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 48

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source=pdf_text observed=2026-08-11T14:34:44.037949Z digest=sha256:1871686c7902385e9417ddeb6f76fe42996d16b478f798cbb4c08b7ec53e3f6e

Observation ff07317d-ff02-4e8f-baf6-4824f636d5db · outbound

This paper cites Pyramid scene parsing network,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Pyramid scene parsing network,

Reference 49

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source=pdf_text observed=2026-08-11T14:34:44.043035Z digest=sha256:133a5ac919ac0cd6cb5fbff153816aed5a1143218fd770f7dc5ca7c046feeb9d

Observation ae3c0055-9c79-40eb-96e9-d36677d57cde · outbound

This paper cites A submarine pipeline segmentation method for noisy forward-looking sonar images using global information and coarse segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A submarine pipeline segmentation method for noisy forward-looking sonar images using global information and coarse segmentation,

Reference 50

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source=pdf_text observed=2026-08-11T14:34:44.047077Z digest=sha256:476701d3e03d6c9acdc10f84b372710d5f19405aae783e6b5c820057f93f20c6

Observation 633f5b84-73c9-4d79-afbe-35d33fa11837 · outbound

This paper cites Side-scan sonar images segmentation for auv with recurrent residual convolutional neural network module and self-guidance module,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Side-scan sonar images segmentation for auv with recurrent residual convolutional neural network module and self-guidance module,

Reference 51

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source=pdf_text observed=2026-08-11T14:34:44.051308Z digest=sha256:3a16f0fc12d0aede40b5a5a73a00a52c37b4d32f27d1cc23d88d34ba322afa2d

Observation abf5f769-1d97-413c-b8f4-415d1e26e238 · outbound

This paper cites Attention u-net: Learning where to look for the pancreas,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Attention u-net: Learning where to look for the pancreas,

Reference 52

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source=pdf_text observed=2026-08-11T14:34:44.055703Z digest=sha256:460622b7b2c016fbe90e63efafbadebc676cf7ee51d1eacd50c6029742b0c792

Observation bbf795bc-ecfc-49e0-a221-b0b82762fa64 · outbound

This paper cites Rethinking semantic segmenta- tion from a sequence-to-sequence perspective with transformers,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Rethinking semantic segmenta- tion from a sequence-to-sequence perspective with transformers,

Reference 53

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source=pdf_text observed=2026-08-11T14:34:44.060428Z digest=sha256:afb0b80cdb25d8784bbe9ef587ccf7285c63ba253812147cc6da8e7314cf2d7d

Observation 67afdd9a-38dd-4c68-a01d-1d7f0b9d0454 · outbound

This paper cites Segmenter: Trans- former for semantic segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Segmenter: Trans- former for semantic segmentation,

Reference 54

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source=pdf_text observed=2026-08-11T14:34:44.065255Z digest=sha256:f5f9df5cf83ca9f5e29c6d1482974a2a7250c5102b84fcd0c07acc3baac9dcf0

Observation 4b8a5cd4-b8bc-4ca4-b1dc-4a3118fc5ad7 · outbound

This paper cites Mitu-net: An efficient mix transformer u-like network for forward-looking sonar image segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Mitu-net: An efficient mix transformer u-like network for forward-looking sonar image segmentation,

Reference 55

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source=pdf_text observed=2026-08-11T14:34:44.069803Z digest=sha256:f38a2ea37dd62f71c11cf52a8389895aff7be8f7b6328df35f83117e674725ad

Observation f0ceca53-529e-426a-8826-75dedf2e93bd · outbound

This paper cites Sonarnet: Hybrid cnn-transformer- hog framework and multifeature fusion mechanism for forward-looking sonar image segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Sonarnet: Hybrid cnn-transformer- hog framework and multifeature fusion mechanism for forward-looking sonar image segmentation,

Reference 56

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source=pdf_text observed=2026-08-11T14:34:44.074523Z digest=sha256:bc48b50ecfc8776f070457b2dd6efee617882da716b1a1188835c35d9ae120c0

Observation 2d33b2ed-38df-4824-a456-c4efbd263320 · outbound

This paper cites Subpipe: A submarine pipeline inspection dataset for segmentation and visual-inertial localization,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Subpipe: A submarine pipeline inspection dataset for segmentation and visual-inertial localization,

Reference 57

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source=pdf_text observed=2026-08-11T14:34:44.078935Z digest=sha256:9259e4e18e791a7f933ce5d988ad032ce1e5310754ebc99e94d0fe809a300643

Observation 7fe929f7-2141-4278-bcc4-1a759886b6a1 · outbound

This paper cites Semantic segmentation of underwater imagery: Dataset and benchmark,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Semantic segmentation of underwater imagery: Dataset and benchmark,

Reference 58

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source=pdf_text observed=2026-08-11T14:34:44.083413Z digest=sha256:47429c0f998a8434b9a5cd83e59b5d32b3a426aacdb66eb4aced8db515e009a0

Observation fd3dd054-4b0a-4d6b-87e0-80903dee66fb · outbound

This paper cites Simultaneous map building and localization for an autonomous mobile robot,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Simultaneous map building and localization for an autonomous mobile robot,

Reference 59

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source=pdf_text observed=2026-08-11T14:34:44.088200Z digest=sha256:12819edf519dba7394d300a46ba0a50dfa2f7ad2fdbe38188e8aa08ebeb8643b

Observation 17dba3c8-2df8-456a-b794-fe914c20f2ef · outbound

This paper cites A new approach to linear filtering and prediction problems,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A new approach to linear filtering and prediction problems,

Reference 60

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source=pdf_text observed=2026-08-11T14:34:44.093237Z digest=sha256:6b0e83fcfedf73352705c3c83b54b8995e70ebea94b1c8cd3de791b3079d84a8

Observation 5448121b-59ab-46bf-892d-b6c01a837514 · outbound

This paper cites A tutorial on graph-based slam,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A tutorial on graph-based slam,

Reference 61

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source=pdf_text observed=2026-08-11T14:34:44.098182Z digest=sha256:ceed5e2b61b01c02369f982abcc6dcf320d0e1e836ef73a19f07e1aa58f4cc6e

Observation b885994c-4406-4c36-968b-f696e6553f1a · outbound

This paper cites Feature-based under- water localization using imaging sonar in confined environments,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Feature-based under- water localization using imaging sonar in confined environments,

Reference 62

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source=pdf_text observed=2026-08-11T14:34:44.102440Z digest=sha256:3699be70ac1a12c79bf06beb75238311b39973609da4bc6bd11a42281a095c00

Observation bf1acc50-4c51-48af-988e-f83399a19fb1 · outbound

This paper cites A fully-automatic side-scan sonar simultaneous localization and mapping framework,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A fully-automatic side-scan sonar simultaneous localization and mapping framework,

Reference 63

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source=pdf_text observed=2026-08-11T14:34:44.106617Z digest=sha256:682c8643d321bd7ea5b7791845c3ff735ef83200bb749dc04f0080561278e244

Observation 71708ec5-f7e0-405d-a7a3-ba19dfd20af9 · outbound

This paper cites Toward Geometric Deep SLAM.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Toward Geometric Deep SLAM

Reference 64

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source=pdf_text observed=2026-08-11T14:34:44.111209Z digest=sha256:1807f651efc881cd1bd032d34f15f2ab3f97689d407230079e647b279e408d74

Observation ea6a1726-2eb8-477a-8afe-0020c185ff38 · outbound

This paper cites Review of underwater slam techniques,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Review of underwater slam techniques,

Reference 65

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source=pdf_text observed=2026-08-11T14:34:44.115814Z digest=sha256:d400380df3c5065260101af95405da3be8cb21cb8a33323e3fc5fddebde8787c

Observation 7f26631a-2605-4a30-a9bf-edbdfa45951f · outbound

This paper cites Visual slam for underwater vehicles: A survey,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Visual slam for underwater vehicles: A survey,

Reference 66

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source=pdf_text observed=2026-08-11T14:34:44.119745Z digest=sha256:f0460c581d4dddc6f81561b6c722e7d1d0301a546f52ca66b0567cf0a196f8fc

Observation 3cc879a5-816c-4c19-92d9-a1316e73aabd · outbound

This paper cites Svin2: A multi-sensor fusion-based underwater slam system,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Svin2: A multi-sensor fusion-based underwater slam system,

Reference 67

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source=pdf_text observed=2026-08-11T14:34:44.123879Z digest=sha256:61576ab1c728edef9eefbbc089177be7cd7399c44083866702764a8c63665605

Observation 27f14b68-0cbc-412b-9c97-43074d8741fd · outbound

This paper cites Svin2: An underwater slam system using sonar, visual, inertial, and depth sensor,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Svin2: An underwater slam system using sonar, visual, inertial, and depth sensor,

Reference 68

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source=pdf_text observed=2026-08-11T14:34:44.128275Z digest=sha256:9bff4c928d28d08202e727e6a9e33eac0760cf887213a4c0d2f6cf0e7ddcc24e

Observation 72d930a6-b756-4281-a25d-e918c700aa4e · outbound

This paper cites Adaptive tuning of a kalman filter via fuzzy logic for an intelligent auv navigation system,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Adaptive tuning of a kalman filter via fuzzy logic for an intelligent auv navigation system,

Reference 69

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source=pdf_text observed=2026-08-11T14:34:44.132405Z digest=sha256:ff7c31763d3a4727502695404456569aa7fec0f5d27157a357790d071f63b638

Observation 2f34f4e6-9cce-42c2-97ca-73990392b4c4 · outbound

This paper cites A dense subframe-based slam framework with side-scan sonar,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A dense subframe-based slam framework with side-scan sonar,

Reference 70

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source=pdf_text observed=2026-08-11T14:34:44.136654Z digest=sha256:e88b4e2a14199e1de47e69a2ed2734fa8f404505c8119abc1701c9828f120c5b

Observation 1dfabc8c-1139-485e-bbde-74c7e98c8bc1 · outbound

This paper cites Savor: Sonar-aided visual odometry and reconstruction for autonomous underwater vehicles,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Savor: Sonar-aided visual odometry and reconstruction for autonomous underwater vehicles,

Reference 71

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source=pdf_text observed=2026-08-11T14:34:44.140478Z digest=sha256:6dea30870f685ea71ffd7160abaf6a35521c8eba36edab87e112bf302af843d3

Observation 5fc16387-f538-4cf5-ba7b-c64166158841 · outbound

This paper cites An overview of key slam technologies for underwater scenes,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges An overview of key slam technologies for underwater scenes,

Reference 72

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source=pdf_text observed=2026-08-11T14:34:44.144550Z digest=sha256:45a33496111fad11978ad7331335e83591ab64bfcb0e1d4db18b6fe427bf7537

Observation 185ecdb2-5694-4f51-9afc-19b8cd35ddf9 · outbound

This paper cites Autonomous underwater vehicle navigation using sonar image matching based on convolutional neural network,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Autonomous underwater vehicle navigation using sonar image matching based on convolutional neural network,

Reference 73

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source=pdf_text observed=2026-08-11T14:34:44.148976Z digest=sha256:ea4009b70ee9e39553e3977faa1b7f7902caaccb5e149439b95cfd896e526390

Observation f96e9abc-4822-4473-82e9-786c9a0a5945 · outbound

This paper cites Diverse ocean noise classifi- cation using deep learning,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Diverse ocean noise classifi- cation using deep learning,

Reference 74

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Observation b23bd96f-9ed2-42a1-8f07-6182113e8a2e · outbound

This paper cites A dataset with multibeam forward- looking sonar for underwater object detection,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A dataset with multibeam forward- looking sonar for underwater object detection,

Reference 75

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Observation ceee9f6b-1455-40cd-8662-c465f149cfa4 · outbound

This paper cites An adaptive denoising and detection approach for underwater sonar image,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges An adaptive denoising and detection approach for underwater sonar image,

Reference 76

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Observation 9973a279-1e2e-474c-8225-f97feb17ed07 · outbound

This paper cites Sonar image denoising based on anisotropic guided filtering,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Sonar image denoising based on anisotropic guided filtering,

Reference 77

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Observation b801ea5e-a3a5-41ab-b5a8-b79684069636 · outbound

This paper cites Deep denoising method for side scan sonar images without high-quality reference data,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Deep denoising method for side scan sonar images without high-quality reference data,

Reference 78

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Observation 5d409296-88da-4b7c-a8ee-2677b3498702 · outbound

This paper cites Remove and recover: two stage convolutional autoencoder based sonar image enhancement algorithm,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Remove and recover: two stage convolutional autoencoder based sonar image enhancement algorithm,

Reference 79

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 24c57384-50b5-4b2e-8c4a-b676019b3e1b · outbound

This paper cites Research on a feature enhancement extraction method for underwater targets based on deep autoencoder networks,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Research on a feature enhancement extraction method for underwater targets based on deep autoencoder networks,

Reference 80

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Observation 513dd393-ca17-480c-8456-8b5924ed47eb · outbound

This paper cites Connectionist Bench (Sonar, Mines vs. Rocks),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Connectionist Bench (Sonar, Mines vs. Rocks),

Reference 81

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Observation 2d791862-4728-4c7b-8040-e20e26deabe6 · outbound

This paper cites Side-scan sonar and wa- ter profiler data from Lago Grey,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Side-scan sonar and wa- ter profiler data from Lago Grey,

Reference 82

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Observation 33f4141a-056b-4371-b52e-ccb85c54e5e5 · outbound

This paper cites Underwater ice terrace observed at the front of glaciar grey, a freshwater calving glacier in patagonia,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Underwater ice terrace observed at the front of glaciar grey, a freshwater calving glacier in patagonia,

Reference 83

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Observation 566c8fb8-3c1b-4ed2-84e5-41a0ad4e6b3c · outbound

This paper cites Ireland’s Open Data Portal,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Ireland’s Open Data Portal,

Reference 84

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Observation 53dd1e05-5c4f-4eb2-8a73-57942c16dc1b · outbound

This paper cites U.S. Government’s Open Data,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges U.S. Government’s Open Data,

Reference 85

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Observation 82732ad6-fe8d-4d6e-87a7-e46ed70402df · outbound

This paper cites Side-scan sonar images of marine engineering geology (Marine PULSE Dataset),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Side-scan sonar images of marine engineering geology (Marine PULSE Dataset),

Reference 86

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Observation 45a217a2-573e-43d9-8362-1aa402a4b632 · outbound

This paper cites Revealing the potential of deep learning for detecting submarine pipelines in side-scan sonar images: An investigation of pre-training datasets,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Revealing the potential of deep learning for detecting submarine pipelines in side-scan sonar images: An investigation of pre-training datasets,

Reference 87

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Observation c2379c9e-cd1c-4f66-a08a-f63c83bd10da · outbound

This paper cites Side Scan Sonar mosaics of selected northern Adriatic mesophotic biogenic reefs off Venice (GeoTIFF image),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Side Scan Sonar mosaics of selected northern Adriatic mesophotic biogenic reefs off Venice (GeoTIFF image),

Reference 88

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Observation 0ff97715-6431-4dd3-a9a5-33c6461b86a8 · outbound

This paper cites Machine learning for shipwreck segmentation from side scan sonar imagery: Dataset and benchmark,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Machine learning for shipwreck segmentation from side scan sonar imagery: Dataset and benchmark,

Reference 89

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Observation 00d89949-7877-48fa-b8a4-78fe62b1ad54 · outbound

This paper cites An acous- tic and optical dataset for the perception of underwater unexploded ordnance (uxo),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges An acous- tic and optical dataset for the perception of underwater unexploded ordnance (uxo),

Reference 90

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Observation 5636f5bf-66b5-4144-8103-71d174b85b2f · outbound

This paper cites A Large Scale Side-Scan Sonar Dataset of Seafloor Sediments for Self-Supervised Pretraining,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges A Large Scale Side-Scan Sonar Dataset of Seafloor Sediments for Self-Supervised Pretraining,

Reference 91

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Observation 14bdfc21-6608-400e-9339-9d5ae01d7270 · outbound

This paper cites Side-scan sonar imaging for Mine detec- tion,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Side-scan sonar imaging for Mine detec- tion,

Reference 92

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Observation 446802d2-8c81-48ff-aa78-7ad65a1de625 · outbound

This paper cites DIDSON fish data and code for analysis,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges DIDSON fish data and code for analysis,

Reference 93

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Observation 256b6e27-4555-4759-95c5-e7b0f2e67bcd · outbound

This paper cites Optimising the workflow for fish detection in didson (dual-frequency identification sonar) data with the use of optical flow and a genetic algorithm,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Optimising the workflow for fish detection in didson (dual-frequency identification sonar) data with the use of optical flow and a genetic algorithm,

Reference 94

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Observation a66c174c-af47-48e4-9227-1658e90564eb · outbound

This paper cites Marine Debris Turntable,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Marine Debris Turntable,

Reference 95

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Observation 3c4e2d47-ada2-4d89-9fd0-bac70baae0af · outbound

This paper cites The marine debris dataset for forward-looking sonar semantic segmentation,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges The marine debris dataset for forward-looking sonar semantic segmentation,

Reference 96

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Observation dc46fcad-8ab9-404d-8c2d-4ae8f71e1e26 · outbound

This paper cites Synthetic aperture sonar seabed environment dataset (sassed),.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Synthetic aperture sonar seabed environment dataset (sassed),

Reference 97

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Observation 4fcffb8d-9e42-4f84-80bb-01274881ff05 · outbound

This paper cites an unresolved cited work.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Unresolved cited work

Reference 98

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Observation 4e3460d4-dd40-4303-a9d4-99c9f048c8ea · outbound

This paper cites Open-set recognition with long-tail sonar images,.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges Open-set recognition with long-tail sonar images,

Reference 99

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Observation 9f7d7746-e64b-4144-890c-6086144eadb0 · outbound

This paper cites ROSAR: An Adversarial Re-Training Framework for Robust Side-Scan Sonar Object Detection.

Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges ROSAR: An Adversarial Re-Training Framework for Robust Side-Scan Sonar Object Detection

Reference 100

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers

Observation 84861189-01e6-41ea-a133-a65038e034a2 · inbound

Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data cites this paper.

Synthetic Enclosed Echoes: A New Dataset to Mitigate the Gap Between Simulated and Real-World Sonar Data Sonar-based Deep Learning in Underwater Robotics: Overview, Robustness and Challenges

Reference 28

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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