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Paper Citation Record · LEDGER

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection

As of 15 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2412.03200.

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

pith.paper-citation-record.v1
2412.03200 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:44:40.074751Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

  • verified exact0
  • verified fuzzy28
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0a4d2d5e-e137-4af2-a70d-565f389a6533 · outbound

This paper cites Deep learning-based fabric defect detection: A review,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Deep learning-based fabric defect detection: A review,

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

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Observation 96526ac3-bc04-4edc-a56a-36ea67f0faa7 · outbound

This paper cites Enhancing landslide segmentation with guide attention mechanism and fast fourier transformer,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Enhancing landslide segmentation with guide attention mechanism and fast fourier transformer,

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:38.786049Z digest=sha256:dacad434e08d565c965488f52601c9fe0eedba58c5d998e7da778fc1a3f49b8d

Observation fbbe2756-5db8-488b-9e73-7a9baeb2f677 · outbound

This paper cites Fourier-fpn: Fourier improves multi-scale feature learning for oriented tiny object detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Fourier-fpn: Fourier improves multi-scale feature learning for oriented tiny object detection,

Reference 3

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raw_fallback, observed 2026-08-11T22:44:42.450345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:38.831543Z digest=sha256:b77c115d9a10c22aa6083c98b04a4ea669b18ee9c2e9f614200ee9c3c31fba40

Observation 59063fae-7af2-404a-9084-5b9275a91dd0 · outbound

This paper cites Fabric defect detection based on transfer learning and improved Faster R-CNN,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Fabric defect detection based on transfer learning and improved Faster R-CNN,

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:38.874736Z digest=sha256:3f07575f33f01a910b3c1f3bd46d44dade55ebf8699398494772d56d45a74521

Observation d50f10c7-d069-4076-ae21-b748d5a780b8 · outbound

This paper cites Enhancing aerial object detection with selective frequency interaction network,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Enhancing aerial object detection with selective frequency interaction network,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:38.980121Z digest=sha256:ae3cb6322ae12807cf8c48c8312ef0a1b08075bb3112b62c0407d214bb283ae9

Observation 6e56bfbb-ef14-440a-997d-70ec678df1bd · outbound

This paper cites LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection LR-FPN: Enhancing Remote Sensing Object Detection with Location Refined Feature Pyramid Network

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.042190Z digest=sha256:4b0f3cdcde93c30d1668afd7a661b301e98fc71d9c4cd72a0f7268a856fb8caa

Observation 78eacf9f-b739-48bb-b6e0-90f7f6831789 · outbound

This paper cites FP-Deeplab: A segmentation model for fabric defect detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection FP-Deeplab: A segmentation model for fabric defect detection,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.114978Z digest=sha256:00889f1380a559efb43017e380c4e0c5d0c90d08e916d458987266dd6346eebf

Observation a97d1c3e-1339-40bc-918c-a23da1a7747c · outbound

This paper cites Advancing pose-guided image synthesis with progressive conditional diffusion models,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Advancing pose-guided image synthesis with progressive conditional diffusion models,

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.145781Z digest=sha256:6351f602a9feac920a85941cb39830b40148b336ff26303e703086fcde1fcc01

Observation 06753170-822d-424f-9951-695f35be16d2 · outbound

This paper cites Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Boosting Consistency in Story Visualization with Rich-Contextual Conditional Diffusion Models

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.184748Z digest=sha256:a8c41e11c2cae0ba3421a435854e566ff0d41a61b272dd91b5b75c22100a67d6

Observation c1edc48c-46c9-4299-8592-f554a1cedd25 · outbound

This paper cites IMAGDressing-v1: Customizable Virtual Dressing.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection IMAGDressing-v1: Customizable Virtual Dressing

Reference 10

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source=pdf_text observed=2026-08-11T22:44:39.234746Z digest=sha256:a99e8d28c567df396b1ab0d2af9f7c69144e935670275f031332c68070183701

Observation d432eb9b-803f-4901-9a21-6899da452e6b · outbound

This paper cites Imagpose: A unified conditional framework for pose-guided person generation,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Imagpose: A unified conditional framework for pose-guided person generation,

Reference 11

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.284753Z digest=sha256:eb64cde6ee1fdf89694c51f997ea904750b8594ceee1c40c6c51a65e2e5f75c8

Observation 2fb852ef-bebe-4537-9f4d-5a26173346f4 · outbound

This paper cites A mixed-attention-based multi-scale autoencoder algorithm for fabric de- fect detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection A mixed-attention-based multi-scale autoencoder algorithm for fabric de- fect detection,

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.324869Z digest=sha256:2853e2f09bcffd47b26f1601aca0acb1c56729675b0584ad1dd173dc5d015c3f

Observation ffb814a4-aae5-4e90-8619-37895350dcc3 · outbound

This paper cites Knowledge distillation for unsupervised defect detection of yarn-dyed fabric using the system DAERD: Dual attention embedded reconstruc- tion distillation,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Knowledge distillation for unsupervised defect detection of yarn-dyed fabric using the system DAERD: Dual attention embedded reconstruc- tion distillation,

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.381985Z digest=sha256:b25ba5e4303de4cc5a0b0f7bca62ed6b2e71b1e615b41163690967876b8ab3ef

Observation 85a96a06-f1ac-42d3-b75c-4197caf87d88 · outbound

This paper cites Automated fabric defect detection using multi-scale fusion MemAE,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Automated fabric defect detection using multi-scale fusion MemAE,

Reference 14

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raw_fallback, observed 2026-08-11T22:44:42.113399Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.434749Z digest=sha256:3b11acff1808b4cb64fd0d6a0ddfe737855864904c037caf8b3ef2a5eb2207f7

Observation a43b6bcb-09ce-45b5-8df3-dc289869e622 · outbound

This paper cites Faster R-CNN: Towards real-time object detection with region proposal net- works,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Faster R-CNN: Towards real-time object detection with region proposal net- works,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.472012Z digest=sha256:3aecae558bd87e1b64ee49cc39efafa13476868a46ba2cb8b6d978d0080ae7c4

Observation bcdd96c6-0d5b-461b-a9df-3a540f59edb4 · outbound

This paper cites ultra- lytics/yolov5. github repository,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection ultra- lytics/yolov5. github repository,

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.515178Z digest=sha256:35980d5bbd32546d13dc1e64eb367807aebb17d6ad5a78adbd07b9b809194a1b

Observation 3d3f39d9-823e-488a-8677-68becf8efe60 · outbound

This paper cites Research on Fabric Defect Detection Algorithm Based on Improved YOLOv8n Algorithm,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Research on Fabric Defect Detection Algorithm Based on Improved YOLOv8n Algorithm,

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.574752Z digest=sha256:3f1df0f0c43684d58314fbc41429923232cfa3a6dc15c0ce97c4a7961fcfb543

Observation 0ea44fb8-f4d8-4770-94b8-4a15e89faa08 · outbound

This paper cites Fabric surface defect detection using SE-ssdnet,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Fabric surface defect detection using SE-ssdnet,

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.614761Z digest=sha256:c7c8ba865f1a13bb8a39dbbf91697c7d3e8e2a73cd784818266cc098593a47e3

Observation ef3597b6-2ec3-40ca-9698-4d2b950f94b4 · outbound

This paper cites A novel multi-frequency coordinated module for sar ship detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection A novel multi-frequency coordinated module for sar ship detection,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.674744Z digest=sha256:ab9bb72b93b4b006e37908671e485f922697f939d2eaded981034c854cd90ba5

Observation 08a13117-7acb-4c48-ba53-2293d3fdeaa4 · outbound

This paper cites A novel cross frequency-domain interaction learning for aerial oriented object detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection A novel cross frequency-domain interaction learning for aerial oriented object detection,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.715730Z digest=sha256:8fd10ea0d47c11a4da06c5059efb7fce096ecd49fc8774978b3f2fdd5427c32c

Observation 6d7f653f-ee74-4552-97ef-54bd2e95515b · outbound

This paper cites PRC-light YOLO: An efficient lightweight model for fabric defect detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection PRC-light YOLO: An efficient lightweight model for fabric defect detection,

Reference 21

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raw_fallback, observed 2026-08-11T22:44:41.084824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.756483Z digest=sha256:8fd781fb63ee3778699f8dd3c43100566a37ab35c3c44224947bfb4783bfd358

Observation 4b4ed8fd-9121-4fd0-a2c7-aebebffc122a · outbound

This paper cites Feature pyramid full granularity attention network for object detection in remote sensing imagery,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Feature pyramid full granularity attention network for object detection in remote sensing imagery,

Reference 22

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raw_fallback, observed 2026-08-11T22:44:40.934851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.804749Z digest=sha256:d21a65a229c67f83bc79984887a6a527ef817af1206b7d2251d3d241cfb256e8

Observation a125d322-dba6-40e6-90c9-8b5bac14c1cf · outbound

This paper cites Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Reference 23

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.854750Z digest=sha256:d290699e738ac4764bdf9cd4b3fac649e49da42be9a1d8cac515b75a50af86da

Observation 22620cb1-8ed5-471d-9110-12afe15a998d · outbound

This paper cites MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection MambaAD: Exploring State Space Models for Multi-class Unsupervised Anomaly Detection

Reference 24

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.887244Z digest=sha256:7cfbc92424ab698f7c352b2e46f08dcb5477d1deabb99fd0c3dc8313ce811edb

Observation fd3dd4e0-5309-4154-a9d5-19cc8fbc1ad9 · outbound

This paper cites VMamba: Visual State Space Model.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection VMamba: Visual State Space Model

Reference 25

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no resolver link, observed 2026-08-11T22:44:39.895183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.895183Z digest=sha256:416bc39ce24864ae8732463fe788a1404a5272c4d22874416f0c153a028b1cfa

Observation eddd8cb3-7705-4a04-ae46-42ad9a2f430d · outbound

This paper cites A review on yolov8 and its advancements,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection A review on yolov8 and its advancements,

Reference 26

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raw_fallback, observed 2026-08-11T22:44:40.778746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.904101Z digest=sha256:099c95505e1054e36dcfdbef8dadc888831c30f9d2e95dd3aed608a243dc3ee9

Observation 7a3f8633-33b7-4bc2-90f8-f04234135b41 · outbound

This paper cites Tph-yolov5: Improved yolov5 based on transformer prediction head for object detection on drone-captured scenarios,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Tph-yolov5: Improved yolov5 based on transformer prediction head for object detection on drone-captured scenarios,

Reference 27

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raw_fallback, observed 2026-08-11T22:44:40.662634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.914677Z digest=sha256:a981c8e14bef8fe1aec521f009e70c1308e204e39b561295ae74d9f8e012b6e6

Observation 71d73ffa-9f27-4264-9c23-15c746176a49 · outbound

This paper cites Eca-net: Efficient channel attention for deep convolutional neural networks,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Eca-net: Efficient channel attention for deep convolutional neural networks,

Reference 28

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no resolver link, observed 2026-08-11T22:44:39.919465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T22:44:39.919465Z digest=sha256:cde04943a1eec5ec9df81bd3452b1df343d8c56a7b5d9269de91fe62d7eca247

Observation 34dfdc39-7e5a-4345-8f58-489b7c8a970d · outbound

This paper cites Attention-Based Multiscale Feature Fusion for Efficient Surface Defect Detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Attention-Based Multiscale Feature Fusion for Efficient Surface Defect Detection,

Reference 29

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raw_fallback, observed 2026-08-11T22:44:40.560895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.926353Z digest=sha256:6d91222cab7e52f979e9adec34faa937eb80f1ca161c27ca42864f2e463967e6

Observation 0dee6653-61ed-4552-9466-fb90b9a85337 · outbound

This paper cites Fabric defect detection via a spatial cloze strategy,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Fabric defect detection via a spatial cloze strategy,

Reference 30

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raw_fallback, observed 2026-08-11T22:44:40.540330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.939940Z digest=sha256:8387ec35f3d34f5f4c1343aa1fe542aa2b15baa9acc5debaabfa18091dd207b3

Observation 6fc5771c-7fff-4c0a-b183-65ba834eafb1 · outbound

This paper cites Tood: Task-aligned one-stage object detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Tood: Task-aligned one-stage object detection,

Reference 31

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raw_fallback, observed 2026-08-11T22:44:40.517473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.948545Z digest=sha256:1cfada21b91f372e23d43c75ae2e31a7a63de548029d5b4533317e9c2055dee0

Observation 96cedad6-8788-43ee-9467-1193f5721349 · outbound

This paper cites An anchor- free defect detector for complex background based on pixelwise adaptive multiscale feature fusion,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection An anchor- free defect detector for complex background based on pixelwise adaptive multiscale feature fusion,

Reference 32

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raw_fallback, observed 2026-08-11T22:44:40.491086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.954098Z digest=sha256:e6e7f0a52153e177d51429f0f77dc301b718ab7472bd638dff6da78a0bfcd216

Observation 72c550c8-d8f4-43f5-8345-9d8953aa4619 · outbound

This paper cites Fabric defect detection based on anchor-free network,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Fabric defect detection based on anchor-free network,

Reference 33

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raw_fallback, observed 2026-08-11T22:44:40.473459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:39.973485Z digest=sha256:00681bb7ebada3897c05714ab5799409714e8ecc147c63a9a7982fd5cec94199

Observation 963e573d-dc9f-40d0-a411-ba1090a31715 · outbound

This paper cites Adaptively Fused Attention Module for the Fabric Defect Detection,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Adaptively Fused Attention Module for the Fabric Defect Detection,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:44:40.450977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:40.014750Z digest=sha256:cb79284f9c374622a64c2f5a7df971262c59b9f79b8561388e5c1368148a6001

Observation 84ec6bd8-4bae-44fc-b7ec-9e9b6e652a9f · outbound

This paper cites Research on Tiny Target Detection Technology of Fabric Defects Based on Improved YOLO,.

Fab-ME: A Vision State-Space and Attention-Enhanced Framework for Fabric Defect Detection Research on Tiny Target Detection Technology of Fabric Defects Based on Improved YOLO,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:44:40.417849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-08-11T22:44:40.074751Z digest=sha256:dec48a456133ca852724c7ef5897849661f2a78a344e3dab23737a85b9b2a5ae

Pith citing papers

No inbound Pith citation observations are available.