Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-09T22:16:15.552649Z
Paper Citation Record · LEDGER
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM
As of 13 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2501.18855.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
48 of 48 outbound references displayed
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- verified fuzzy44
- unresolved4
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 7ce8d3c5-2b20-4add-bbfc-059db9075187 · outbound
This paper cites Automation in road distress detection, diagnosis and treatment,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Automation in road distress detection, diagnosis and treatment,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.175921Z
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.
Observation b2f0c982-64f1-4702-88d4-45b016a5c210 · outbound
This paper cites A universal multi-view guided network for salient object and camouflaged object detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM A universal multi-view guided network for salient object and camouflaged object detection,
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.164254Z
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.
Observation 91e19569-93ea-41c1-bb14-b068b040f07f · outbound
This paper cites Computer vision frame- work for crack detection of civil infrastructure—a review,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Computer vision frame- work for crack detection of civil infrastructure—a review,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.152380Z
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.
Observation 30a9d06e-131c-4769-9dcf-0325234a0c84 · outbound
This paper cites Erdunet: An efficient residual double- coding unet for medical image segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Erdunet: An efficient residual double- coding unet for medical image segmentation,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.139743Z
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.
Observation dd24ecdd-3098-418f-b6d3-c91319b528ee · outbound
This paper cites Pixel dif- ference convolutional network for rgb-d semantic segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Pixel dif- ference convolutional network for rgb-d semantic segmentation,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.128979Z
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.
Observation 1b5339ed-7d00-4140-91c3-fa89464a59be · outbound
This paper cites Boosting salient object detection with transformer-based asymmetric bilateral u-net,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Boosting salient object detection with transformer-based asymmetric bilateral u-net,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.117127Z
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.
Observation 18c88083-e192-43a7-a303-ca1f2ef0f6ff · outbound
This paper cites Hybrid semantic segmentation for tunnel lining cracks based on swin transformer and convolutional neural network,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Hybrid semantic segmentation for tunnel lining cracks based on swin transformer and convolutional neural network,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.105831Z
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.
Observation e27112de-e792-4766-ae01-615e96d8d2cb · outbound
This paper cites Ctif-net: A cnn- transformer iterative fusion network for salient object detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Ctif-net: A cnn- transformer iterative fusion network for salient object detection,
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.092872Z
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.
Observation 6cc79d9e-606f-49af-8eb4-9b08dd4b927c · outbound
This paper cites Small sample image segmen- tation by coupling convolutions and transformers,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Small sample image segmen- tation by coupling convolutions and transformers,
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.077774Z
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.
Observation 1e79d4ec-3a65-45f7-9a48-319ceb716d1e · outbound
This paper cites Ghostformer: Efficiently amal- gamated cnn-transformer architecture for object detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Ghostformer: Efficiently amal- gamated cnn-transformer architecture for object detection,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.063117Z
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.
Observation d3c2cd3a-95a7-4e9f-9816-ef77a7c60c8a · outbound
This paper cites Long-short range adaptive transformer with dynamic sampling for 3d object detec- tion,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Long-short range adaptive transformer with dynamic sampling for 3d object detec- tion,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.048611Z
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.
Observation dc04a9df-5bc7-4106-a2eb-22ef41b5846c · outbound
This paper cites A state-of-the- art survey of deep learning models for automated pavement crack segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM A state-of-the- art survey of deep learning models for automated pavement crack segmentation,
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.035018Z
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.
Observation d5b945d8-1998-4075-bc36-688ca7a5c0d2 · outbound
This paper cites Automatic concrete defect detection and reconstruction by aligning aerial images onto semantic-rich building information model,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Automatic concrete defect detection and reconstruction by aligning aerial images onto semantic-rich building information model,
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.021710Z
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.
Observation f42468c0-9b51-4dd4-a60a-7a814139ca11 · outbound
This paper cites Data augmentation in classification and segmentation: A survey and new strategies,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Data augmentation in classification and segmentation: A survey and new strategies,
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:16.008609Z
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.
Observation 2223f92b-fdfe-4048-8884-553287724f6b · outbound
This paper cites Understanding and combating robust overfitting via input loss landscape analysis and regularization,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Understanding and combating robust overfitting via input loss landscape analysis and regularization,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.995172Z
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.
Observation 3056d31e-2043-404a-a0a4-394af79733c7 · outbound
This paper cites Gpt-3: What’s it good for?.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Gpt-3: What’s it good for?
Reference 16
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4039a657-6aee-4e76-8699-49abc2103fba · outbound
This paper cites Learning transferable visual models from natural language supervision,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Learning transferable visual models from natural language supervision,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.974593Z
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.
Observation c7c44190-6888-40d3-a59c-5df6b21ab389 · outbound
This paper cites Segment anything,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Segment anything,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.961938Z
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.
Observation 528ef723-de5b-4754-9b1f-da5f7963e094 · outbound
This paper cites Detect any shadow: Segment anything for video shadow detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Detect any shadow: Segment anything for video shadow detection,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.950083Z
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.
Observation 4874e062-42af-4440-9092-42650cf23332 · outbound
This paper cites Sam-adapter: Adapting segment anything in underperformed scenes,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Sam-adapter: Adapting segment anything in underperformed scenes,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.938504Z
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.
Observation bd2d4f0d-cd93-49e7-8f16-5f8881bf7163 · outbound
This paper cites Segment anything model for medical image analysis: an experimental study,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Segment anything model for medical image analysis: an experimental study,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.928056Z
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.
Observation 0e28482b-6d34-4bfa-96cd-6bc50f8e9f3a · outbound
This paper cites Segment and caption anything,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Segment and caption anything,
Reference 22
- Resolution
- verified fuzzy
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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.
Observation 84e0ab90-66dc-48ac-b5e8-cb963eb52f34 · outbound
This paper cites Teaching segment- anything-model domain-specific knowledge for road crack segmentation from on-board cameras,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Teaching segment- anything-model domain-specific knowledge for road crack segmentation from on-board cameras,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.905426Z
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.
Observation 8e2435d7-b97d-42c6-b97a-8b3eaa37d8d8 · outbound
This paper cites EdgeSAM: Prompt-In-the-Loop Distillation for SAM.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM EdgeSAM: Prompt-In-the-Loop Distillation for SAM
Reference 24
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6c4cd85-8594-4aa2-94e2-2d90f31beb92 · outbound
This paper cites Ecsnet: An accelerated real-time image segmentation cnn architecture for pavement crack detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Ecsnet: An accelerated real-time image segmentation cnn architecture for pavement crack detection,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.891831Z
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.
Observation ba2ad3af-8887-4316-8e07-3ff501c917f7 · outbound
This paper cites Crackvit: a unified cnn-transformer model for pixel-level crack extraction,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Crackvit: a unified cnn-transformer model for pixel-level crack extraction,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.878415Z
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.
Observation 982fba30-1b23-4149-a741-4d174fadb364 · outbound
This paper cites A hybrid deep learning pavement crack semantic segmen- tation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM A hybrid deep learning pavement crack semantic segmen- tation,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.865392Z
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.
Observation 0e3da90c-e19e-4c64-96a6-167e7f0c0fac · outbound
This paper cites Fully convolutional networks for semantic segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Fully convolutional networks for semantic segmentation,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.852415Z
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.
Observation 93b871f4-29b8-40d3-8ff0-8852106f889b · outbound
This paper cites U-net: Convolutional networks for biomedical image segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM U-net: Convolutional networks for biomedical image segmentation,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.837979Z
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.
Observation dfcc63ef-31aa-4bc2-a291-53b74a7ebcb3 · outbound
This paper cites Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Segnet: A deep con- volutional encoder-decoder architecture for image segmentation,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.824618Z
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.
Observation 3ed86fa7-a9d3-4b38-83c7-dae80b253f00 · outbound
This paper cites Tv-net: A structure- level feature fusion network based on tensor voting for road crack segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Tv-net: A structure- level feature fusion network based on tensor voting for road crack segmentation,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.811540Z
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.
Observation a5e6d1dc-9144-447e-a2ad-8ab722ef069b · outbound
This paper cites A nested unet with attention mechanism for road crack image segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM A nested unet with attention mechanism for road crack image segmentation,
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.798036Z
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.
Observation 89cbcc21-29de-4b39-a52d-23b009efe934 · outbound
This paper cites Vision transformers for dense prediction,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Vision transformers for dense prediction,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.784525Z
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.
Observation 0eae8248-c6a5-45d5-b35e-acb974c738c3 · outbound
This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Segformer: Simple and efficient design for semantic segmentation with transformers,
Reference 34
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 81f08926-6a2a-43e1-b1e4-e7a88630a665 · outbound
This paper cites Vision transformer-based autonomous crack detection on asphalt and concrete surfaces,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Vision transformer-based autonomous crack detection on asphalt and concrete surfaces,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.764334Z
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.
Observation c0a4cc10-d9d5-488d-8074-de770eb7e4c0 · outbound
This paper cites A convolutional-transformer network for crack segmentation with boundary awareness,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM A convolutional-transformer network for crack segmentation with boundary awareness,
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.751881Z
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.
Observation bc194ccd-66f8-4bb7-a759-5db2deb149cd · outbound
This paper cites Parameter-efficient transfer 13 learning for nlp,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Parameter-efficient transfer 13 learning for nlp,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.739957Z
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.
Observation 48ba8e15-4c32-487c-8a17-69bdb83c338b · outbound
This paper cites Deepcrack: A deep hierarchical feature learning architecture for crack segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Deepcrack: A deep hierarchical feature learning architecture for crack segmentation,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.728500Z
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.
Observation 5839aceb-3695-4455-8a9d-7938052ce5ad · outbound
This paper cites Automatic road crack detection using random structured forests,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Automatic road crack detection using random structured forests,
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.716891Z
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.
Observation 30b504b3-18be-44e6-84ff-d2898a638add · outbound
This paper cites Feature pyramid and hierarchical boosting network for pavement crack detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Feature pyramid and hierarchical boosting network for pavement crack detection,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.703628Z
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.
Observation ff4a2632-f499-4151-b6a8-44f4c1d1b7e1 · outbound
This paper cites Pyramid scene parsing network,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Pyramid scene parsing network,
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.691030Z
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.
Observation b2dfaf6f-f15c-4e2a-8eef-25234390f277 · outbound
This paper cites Encoder- decoder with atrous separable convolution for semantic image segmen- tation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Encoder- decoder with atrous separable convolution for semantic image segmen- tation,
Reference 42
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e43b55c-3f7d-4341-9b98-d44a8ae1979b · outbound
This paper cites Emcad: Efficient multi- scale convolutional attention decoding for medical image segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Emcad: Efficient multi- scale convolutional attention decoding for medical image segmentation,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.668581Z
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.
Observation 79c245ce-4c46-47dc-91a0-4f12e14c6f0d · outbound
This paper cites Multi-scale high-resolution vision transformer for semantic segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Multi-scale high-resolution vision transformer for semantic segmentation,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.654906Z
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.
Observation a19c16ad-200d-4e11-ab66-78f6de0412db · outbound
This paper cites Cmtfnet: Cnn and multiscale transformer fusion network for remote sensing image semantic segmentation,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Cmtfnet: Cnn and multiscale transformer fusion network for remote sensing image semantic segmentation,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.641756Z
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.
Observation 964b6139-3e96-477e-9393-22831fedaec1 · outbound
This paper cites Deepcrack: Learning hierarchical convolutional features for crack detection,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Deepcrack: Learning hierarchical convolutional features for crack detection,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.628618Z
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.
Observation 2d17e920-0d77-4f3d-910d-2e0fdeb20cb6 · outbound
This paper cites Deepcrackat: An effective crack segmentation framework based on learning multi-scale crack features,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Deepcrackat: An effective crack segmentation framework based on learning multi-scale crack features,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.615631Z
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.
Observation dcce22b5-8c7a-4b24-a073-7fcf8015ecc7 · outbound
This paper cites Topology-aware mamba for crack segmentation in structures,.
FlexiCrackNet: A Flexible Pipeline for Enhanced Crack Segmentation with General Features Transfered from SAM Topology-aware mamba for crack segmentation in structures,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-09T22:16:15.601750Z
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.
Pith citing papers
No inbound Pith citation observations are available.