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Paper Citation Record · LEDGER

RDD4D: 4D Attention-Guided Road Damage Detection And Classification

As of 15 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 0 inbound Pith citation observations for arXiv:2501.02822.

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

pith.paper-citation-record.v1
2501.02822 v1

Coverage vector

measured 84 of 84 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:07:44.641660Z

measured 84 of 84 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 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

84 of 84 outbound references displayed

  • verified exact10
  • verified fuzzy31
  • unresolved38
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c0df04b6-2ffb-4b6e-8065-5366a2f74701 · outbound

This paper cites Deep learning-based road damage detection and classification for multiple countries,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Deep learning-based road damage detection and classification for multiple countries,

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation db13bd08-9a03-4864-9fb1-0c0f2f2a8e81 · outbound

This paper cites A deep learning approach for road damage detection from smartphone images,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification A deep learning approach for road damage detection from smartphone images,

Reference 2

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d660c141-867e-4162-ba4a-021c1eaf310c · outbound

This paper cites Highway mileage - united states 1990-2020,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Highway mileage - united states 1990-2020,

Reference 3

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3702cbe4-d143-4029-906f-f7c3646442a2 · outbound

This paper cites Study: Pothole damage costs u.s. drivers $3b a year,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Study: Pothole damage costs u.s. drivers $3b a year,

Reference 4

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no resolver link, observed 2026-08-10T22:07:44.335053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 05fa7d62-c6a9-4e03-b931-d30d458c80c5 · outbound

This paper cites The importance of road maintenance,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification The importance of road maintenance,

Reference 5

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.515802Z

Source-reported events for the cited work

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

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Observation cbbd4249-fdb4-4b28-ac15-80f27f0effc5 · outbound

This paper cites A real-time 3d scanning system for pavement distortion inspection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification A real-time 3d scanning system for pavement distortion inspection,

Reference 6

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.502397Z

Source-reported events for the cited work

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

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Observation 14824ef3-ddc1-40fa-ad65-cb6d4dba3fef · outbound

This paper cites Vibration-based system for pavement condition evaluation,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Vibration-based system for pavement condition evaluation,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.489808Z

Source-reported events for the cited work

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

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Observation 7b0a1961-b76a-4892-93ff-5b5d07975091 · outbound

This paper cites Automated pixel-level pavement crack detection on 3d asphalt surfaces with a recurrent neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automated pixel-level pavement crack detection on 3d asphalt surfaces with a recurrent neural network,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.477481Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.351007Z digest=sha256:f7d80eb9d1fd75b9736081d3d083232937ac7c8077ef8dd64e87ac27cfdf8471

Observation c126bea2-a6a7-463d-b087-def8069e89fe · outbound

This paper cites Road damage detection and classification using deep neural networks with smartphone images,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Road damage detection and classification using deep neural networks with smartphone images,

Reference 9

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.465483Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.354683Z digest=sha256:40ccf5c0cd81978ee2ce67c002b9271cafc82f4460f850150f8afd1ca3fd69df

Observation cfa5921e-274c-46c8-96fb-c2211964eca5 · outbound

This paper cites Road crack detection using deep convolutional neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Road crack detection using deep convolutional neural network,

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.452783Z

Source-reported events for the cited work

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

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Observation eb53bdd8-9a8c-4f24-b702-668be8bfc773 · outbound

This paper cites Simultaneous traffic sign detection and boundary estimation using convolutional neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Simultaneous traffic sign detection and boundary estimation using convolutional neural network,

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c9f3d7ab-ccf9-4032-b71b-9d46d070fdea · outbound

This paper cites Bim-based traffic analysis and simulation at road intersection design,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Bim-based traffic analysis and simulation at road intersection design,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.432100Z

Source-reported events for the cited work

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

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Observation 26382d3b-ae42-4414-8c46-fef5fc35cd32 · outbound

This paper cites Transformers in pedestrian image retrieval and person re-identification in a multi-camera surveillance system,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Transformers in pedestrian image retrieval and person re-identification in a multi-camera surveillance system,

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.419655Z

Source-reported events for the cited work

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

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Observation 885ac342-073b-48dd-ba10-4dc539b5cbc1 · outbound

This paper cites Towards open world object detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Towards open world object detection,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.406771Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.371985Z digest=sha256:92af5e6c09e588d598114d590e062aaa8feada4e556687495fd9d33dd27b41e1

Observation a7121f4e-4971-4d4b-8274-78995d7d429a · outbound

This paper cites Comprehensive performance indicators for road pavement condition assessment,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Comprehensive performance indicators for road pavement condition assessment,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.393875Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.375385Z digest=sha256:b1f9b047c1fc822b0fe3c5c4da5e021f222eeedd0a572a5a210ce4293371445b

Observation 37b5aaf0-9013-4649-af78-861d97b44be0 · outbound

This paper cites Detection of multiple road defects for pavement condition assessment,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Detection of multiple road defects for pavement condition assessment,

Reference 16

Resolution
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raw_fallback, observed 2026-08-10T22:07:46.379640Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.379078Z digest=sha256:df3fd2d8283caeecffa5c059dc3dcf87f041df5032ddaa658f72a484b5228f00

Observation ea87c77d-e587-4db6-9825-7d3dc48e036f · outbound

This paper cites A fast and adaptive road defect detection approach using computer vision with real time implementation,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification A fast and adaptive road defect detection approach using computer vision with real time implementation,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.368330Z

Source-reported events for the cited work

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

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Observation 149e76b7-4e81-48d2-9da6-d27b9dc0a4e0 · outbound

This paper cites Pavement crack detection using otsu thresholding for image segmentation,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Pavement crack detection using otsu thresholding for image segmentation,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.357529Z

Source-reported events for the cited work

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

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Observation b4171cba-828d-4df9-be0a-96cceac4f4d5 · outbound

This paper cites Road crack detection using support vector machine (svm) and otsu algorithm,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Road crack detection using support vector machine (svm) and otsu algorithm,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.346378Z

Source-reported events for the cited work

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

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Observation 8f52a38d-5169-409e-b50c-55caad825ab5 · outbound

This paper cites Pavement crack detec- tion and analysis for high-grade highway,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Pavement crack detec- tion and analysis for high-grade highway,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.334944Z

Source-reported events for the cited work

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

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Observation a2026083-ecf6-495d-ad7a-2a4e5796fd51 · outbound

This paper cites an unresolved cited work.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Unresolved cited work

Reference 21

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unresolved
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Source-reported events for the cited work

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

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Observation c32270fd-0f6a-4d43-8706-26281fe41075 · outbound

This paper cites Detection and segmentation of cement concrete pavement pothole based on image processing tech- nology,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Detection and segmentation of cement concrete pavement pothole based on image processing tech- nology,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.311876Z

Source-reported events for the cited work

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

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Observation 56949144-6428-4842-bc4d-97d205005f77 · outbound

This paper cites Evaluating pavement cracks with bidimensional empirical mode decomposition,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Evaluating pavement cracks with bidimensional empirical mode decomposition,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.300219Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.403149Z digest=sha256:c19cb84e781e501b297a5603af5704a2b5ae0952f4b2794e6cb95f0cf9fa4282

Observation 931af81b-ba31-44f2-919e-b13cc0ec9d70 · outbound

This paper cites Automated pixel-level pavement crack detection on 3d asphalt surfaces using a deep-learning network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automated pixel-level pavement crack detection on 3d asphalt surfaces using a deep-learning network,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.287735Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.406576Z digest=sha256:7543b3528e02a772579c2f214d65d23e7135c5a251a63536c72be55733ea475a

Observation ee839aa0-3db2-4316-93f4-d69dfe894e5f · outbound

This paper cites An approach for the automated extraction of road surface distress from a uav-derived point cloud,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification An approach for the automated extraction of road surface distress from a uav-derived point cloud,

Reference 25

Resolution
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no resolver link, observed 2026-08-10T22:07:44.414037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.414037Z digest=sha256:0a776bae2add54b9c79a652b4148cf4f06fa3f9766238117d99d5237223b3266

Observation 68f7e642-dee1-4a64-987c-61fc710d9666 · outbound

This paper cites Road crack detection using deep convolutional neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Road crack detection using deep convolutional neural network,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.275334Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.417414Z digest=sha256:d8eaef9f79efc74a6000a62754f4ab7b8bd35f9299d382aa3960f5cf237298dd

Observation 27ebed45-526b-4a48-b1b7-d38f9c99d56b · outbound

This paper cites Concrete cracks detection based on deep learning image classification,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Concrete cracks detection based on deep learning image classification,

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.424957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d5ad67ad-af36-4e8e-a799-f14ca7b30516 · outbound

This paper cites Crack-pot: Autonomous road crack and pothole detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Crack-pot: Autonomous road crack and pothole detection,

Reference 28

Resolution
metadata mismatch
raw_fallback, observed 2026-08-10T22:07:45.831385Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.428396Z digest=sha256:406381b0d879ea9f29becca5dc57970a9516d087e043b7d0f8a3a788ea361b92

Observation 110ca3a5-8c64-4e86-af8f-30e4d06a621d · outbound

This paper cites Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural Network.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automatic Pavement Crack Detection Based on Structured Prediction with the Convolutional Neural Network

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.431911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.431911Z digest=sha256:47f832f499013772e266b2a384654e3567fc352901468d54e22e223239e71819

Observation 5c6c49b2-92c3-4190-9de8-803cfa8ecb25 · outbound

This paper cites Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automatic recognition of asphalt pavement cracks using metaheuristic optimized edge detection algorithms and convolution neural network,

Reference 30

Resolution
verified exact
doi, observed 2026-08-10T22:07:44.802803Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.435966Z digest=sha256:506b2a2da4b3b178116cb9f48f7346549fe1ec5babca3cd453d0a4a10f05b341

Observation f01a0b13-2448-4ef9-8dc9-9bebe0ddd6b3 · outbound

This paper cites Attention-guided analysis of infrastructure damage with semi-supervised deep learning,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Attention-guided analysis of infrastructure damage with semi-supervised deep learning,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.439646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.439646Z digest=sha256:29e5cef4e3453d0ec2a9a4aa864df74b68f0a9ae1f578cadd03609c33388288c

Observation e39131b5-439b-4d69-ad10-0443bea006a9 · outbound

This paper cites Automated pixel-level pavement distress detection based on stereo vision and deep learning,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automated pixel-level pavement distress detection based on stereo vision and deep learning,

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.443318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.443318Z digest=sha256:9083a88f8310215ed9fb75962ff7df32403552478010cc90376b043504f32739

Observation 2b33dfd2-8e7d-4f50-95c1-461bc969ae57 · outbound

This paper cites Smart patrolling: An efficient road surface monitoring using smartphone sensors and crowdsourcing,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Smart patrolling: An efficient road surface monitoring using smartphone sensors and crowdsourcing,

Reference 34

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verified exact
doi, observed 2026-08-10T22:07:44.784486Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.450630Z digest=sha256:7a6f19e0b7ec397749afe03c2090c96e44dd40777db48bc8dbb8e9692c5834c1

Observation 2f9830f2-b8c2-45d2-9c68-3cfe5106eb15 · outbound

This paper cites City-wide road distress monitoring with smartphones,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification City-wide road distress monitoring with smartphones,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.262152Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.454024Z digest=sha256:53ff9ce218d1b4dd583b7e8452d6f6c32e666322fb4b4422a57bbabf1f48c7bf

Observation f888c13b-5897-4eab-86dd-fef909977708 · outbound

This paper cites Detection and localization of potholes in roadways using smartphones,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Detection and localization of potholes in roadways using smartphones,

Reference 36

Resolution
verified exact
doi, observed 2026-08-10T22:07:44.772997Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.457669Z digest=sha256:bc45bb5d700402276b3f44f4d1c18d509a78013536fddfb55dd1153b83585891

Observation 5d50d500-c444-4c8b-8598-06f01b1c14aa · outbound

This paper cites Road damage detection and classification using deep neural networks with smartphone images,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Road damage detection and classification using deep neural networks with smartphone images,

Reference 37

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.461158Z digest=sha256:c53a63d895fc8076e99b4602cf9fff843ba2c8b578c9216a3180c2fb5fd19d5a

Observation 8ab1698c-88f7-4a8b-9cc0-937ed8b701cd · outbound

This paper cites Angulo, J.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Angulo, J

Reference 38

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verified exact
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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.464804Z digest=sha256:bba2b7fe985337915422573d8ce218b236db1e87246d6f170af321da948d3b13

Observation b3db0a17-d35b-4617-80e2-5a79559bed9b · outbound

This paper cites Towards low-cost pavement condition health monitoring and analysis using deep learning,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Towards low-cost pavement condition health monitoring and analysis using deep learning,

Reference 39

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doi, observed 2026-08-10T22:07:44.738002Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.468524Z digest=sha256:8742244cfdddb402789ce87ca835ae93b5dcff75cf0097b76ba40d0551cf5aff

Observation 90c316cd-4e6b-4eca-965f-efbca9001d25 · outbound

This paper cites Pavement distress detection and classification based on yolo network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Pavement distress detection and classification based on yolo network,

Reference 40

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raw_fallback, observed 2026-08-10T22:07:45.507644Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.472199Z digest=sha256:1fd6beda95e86db4f8e3f4134f88daa982b58d654bd6747579859e5e81afa641

Observation 48ede051-699e-439c-9618-7dc9024737fb · outbound

This paper cites Pavement image datasets: A new benchmark dataset to classify and densify pavement distresses,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Pavement image datasets: A new benchmark dataset to classify and densify pavement distresses,

Reference 41

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raw_fallback, observed 2026-08-10T22:07:46.248134Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.475442Z digest=sha256:33911371dc9f57871c6734eef8cbbb94c23c0b644ec159421d1218bd91747ef4

Observation 82a6b242-e934-4b67-8285-9e75b2f136c6 · outbound

This paper cites Potspot: Participatory sensing based monitoring system for pothole detection using deep learning,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Potspot: Participatory sensing based monitoring system for pothole detection using deep learning,

Reference 42

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.484373Z digest=sha256:3ccf5f87ce4ee5c9e6373de7e97c276c88cc1c75bd0da3f1f6d935acc0f60eb7

Observation 20b25484-7ccf-49d4-8fa9-1ae9339f510b · outbound

This paper cites Deep learning-based road damage detection and classification for multiple countries,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Deep learning-based road damage detection and classification for multiple countries,

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.488077Z digest=sha256:8d2862e5efa0673a25f97cba52adbe31203124a3036cf2ea1086af26143d390b

Observation 421d19c1-e7d7-4c29-a339-1642096e682f · outbound

This paper cites Crackit: An image processing toolbox for crack detection and characterization,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Crackit: An image processing toolbox for crack detection and characterization,

Reference 45

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metadata mismatch
raw_fallback, observed 2026-08-10T22:07:45.373417Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.495540Z digest=sha256:c0b7c4c73ff9757e481e89f491c2bb5ca8efa6ba6087ff06f232ce73404f1a44

Observation 5d33977e-47c1-493d-b1f0-eea633af8dbb · outbound

This paper cites Automatic road crack detection using random structured forests,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automatic road crack detection using random structured forests,

Reference 46

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raw_fallback, observed 2026-08-10T22:07:46.235926Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.499138Z digest=sha256:db674ce9e77f5c9d3b998dc831e06fe2d63d39c17efed3bf3766b803eea816da

Observation 8ec2f1da-7d84-4be8-9a80-1ba93928e2c4 · outbound

This paper cites Cracktree: Automatic crack detection from pavement images,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Cracktree: Automatic crack detection from pavement images,

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.506340Z digest=sha256:a9736e22a0701490cda9ac55c43fc4654fa5d56483e1891f36ed9beb730d1497

Observation 66276ebc-b2d5-4391-a053-cf0f700dc0e8 · outbound

This paper cites Segment-based pavement crack quantification,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Segment-based pavement crack quantification,

Reference 48

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verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.223780Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.510233Z digest=sha256:2cad044edf8325e65131f8bd58ed991e39e1e7a46409b22b80eab36852e0fc8e

Observation d52bafec-bd0f-4f27-99e9-b0decbd49476 · outbound

This paper cites Sdnet2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Sdnet2018: An annotated image dataset for non-contact concrete crack detection using deep convolutional neural networks,

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.517632Z digest=sha256:55cd651265a55dba4f337ed23fb724ce8a62af9b249c280d31c8455f0c86c902

Observation 34742788-7133-43cf-9701-f784c2fbf903 · outbound

This paper cites Available: http://dx.doi.org/10.1109/TITS.2016.2552248.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: http://dx.doi.org/10.1109/TITS.2016.2552248

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.502870Z digest=sha256:1ede78c795ca07d4e1bf010c61e4c32af2546eea575f056920f09333f91a243f

Observation d53713b5-694c-4bf7-867f-356f72990a1e · outbound

This paper cites Feature pyramid and hierarchical boosting network for pavement crack detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Feature pyramid and hierarchical boosting network for pavement crack detection,

Reference 51

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.524609Z digest=sha256:d034226004b81d70ea054202387d1a994db9df36a730c596e75c5bcd3bd777e9

Observation 2e9bb690-ea61-480a-96d1-6a14139b7357 · outbound

This paper cites A cost effective solution for pavement crack inspection using cameras and deep neural networks,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification A cost effective solution for pavement crack inspection using cameras and deep neural networks,

Reference 52

Resolution
metadata mismatch
raw_fallback, observed 2026-08-10T22:07:45.163743Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.528036Z digest=sha256:21432d348f9adf3cd187a753155e7e9198c08c71067f136ef828edbbec3188f7

Observation b504768b-1f25-4f13-abda-1bf904589520 · outbound

This paper cites How to get pavement distress detection ready for deep learning? a systematic approach,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification How to get pavement distress detection ready for deep learning? a systematic approach,

Reference 53

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no resolver link, observed 2026-08-10T22:07:44.531596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.531596Z digest=sha256:28197fe3a6c9ee507f551f8dbbe612fb6416fb437ffd7f29cb018da07836a79d

Observation 0d83bee0-f402-499a-8ef2-c9ca106fdd36 · outbound

This paper cites Improving visual road condition assessment by extensive experiments on the extended gaps dataset,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Improving visual road condition assessment by extensive experiments on the extended gaps dataset,

Reference 54

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.535208Z digest=sha256:76b14e95a3bd994c8a00497867b36636850685df197e4df32863fcb7fa43bc47

Observation 20abdbd4-e110-4c8d-9055-79187c9d3749 · outbound

This paper cites Automatic pavement crack recognition based on bp neural network,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Automatic pavement crack recognition based on bp neural network,

Reference 55

Resolution
verified exact
doi, observed 2026-08-10T22:07:44.695592Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.521037Z digest=sha256:96100dff3eecaae16b22b35a2d97cac54fc6a2ae7db04c175ed7ec8a7aacf181

Observation 9c3aa6bb-c790-4b0f-88c1-a51774b3cc83 · outbound

This paper cites Beyond bounding- box: Convex-hull feature adaptation for oriented and densely packed object detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Beyond bounding- box: Convex-hull feature adaptation for oriented and densely packed object detection,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.211687Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.543442Z digest=sha256:71d66bb84d88f2f93f22b7ad0d4e26113d41978c3bff1d64d113f21874e6790b

Observation 32d0e147-f841-4500-9f62-8242879bdb4f · outbound

This paper cites Feature pyramid networks for object detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Feature pyramid networks for object detection,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.199318Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.547293Z digest=sha256:612103f3ed5ad4a04c85eae57a0e778342cd1f97cd362d324d2d640af2ef5d46

Observation 3666f897-6164-4d84-8429-99716db7900e · outbound

This paper cites Path aggregation network for instance segmentation,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Path aggregation network for instance segmentation,

Reference 58

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no resolver link, observed 2026-08-10T22:07:44.551158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.551158Z digest=sha256:5e0f7ec75e0cc85fca7df46fe868f7034643f934f56fb96bb2124c0c9177b9d4

Observation 3c122ec8-7a1d-43d2-a19b-7eba7513383b · outbound

This paper cites Conditional convolutions for instance segmentation,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Conditional convolutions for instance segmentation,

Reference 59

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.554819Z digest=sha256:d214f9bc30ab02425e4aef117c9c4ad9ba3c87c8cae702f17f240597769065f9

Observation 176bbbab-5cfa-444c-bdef-1f6478a6c58d · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 60

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no resolver link, observed 2026-08-10T22:07:44.539226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.539226Z digest=sha256:d47c772fc5541c45e7c87e6443ce3b3f7acf9d5538034583c5abe0985e381a54

Observation 4c7e384a-20f2-4a22-a764-a3791792c851 · outbound

This paper cites Focal Loss for Dense Object Detection.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Focal Loss for Dense Object Detection

Reference 61

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.562713Z digest=sha256:86794accc09c83629344c493fa087fbb8d600b5a090913286b170c14ca33e14b

Observation 077c0656-a10f-4369-add9-ac261521e7b0 · outbound

This paper cites Fully convolutional one-stage 3d object detection on lidar range images,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Fully convolutional one-stage 3d object detection on lidar range images,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.158840Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.566889Z digest=sha256:67675ab42b1a4bbc0f7374e90a8fbf563da9e2943bc9119c36cb8599a6306d4a

Observation 70022504-31f5-446d-a5c5-931dbce616a1 · outbound

This paper cites End-to-end object detection with transformers,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification End-to-end object detection with transformers,

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.570776Z digest=sha256:c139597a72c09ddff78dde18dd8dbb51ce92600e7a405de837561f6ef91e13dc

Observation fbdd6d97-f401-43df-98fe-4385a56fc77b · outbound

This paper cites Ota: Optimal transport assignment for object detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Ota: Optimal transport assignment for object detection,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.135579Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.574325Z digest=sha256:dba7e7b14599358a7560c2369772f1d5e9313bf398d8b1e8235771484714eb83

Observation 5c871450-edb1-4254-afc3-b2b4200f4090 · outbound

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

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Tood: Task- aligned one-stage object detection,

Reference 65

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no resolver link, observed 2026-08-10T22:07:44.558602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.558602Z digest=sha256:67dbacf4f16786dbb0c6fe18d78b6922fc2d71b0f6431965a2627685238d482f

Observation c86a7d4a-2b46-48b6-a4a0-e729c43f8e2d · outbound

This paper cites Rtmdet: An empirical study of designing real-time object detectors,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Rtmdet: An empirical study of designing real-time object detectors,

Reference 66

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no resolver link, observed 2026-08-10T22:07:44.582437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.582437Z digest=sha256:67a4772a672f77e8d6fe3070cc46e4017ed195f316ed5dadad8feb299fce00cb

Observation a85ad725-2ee8-4f15-9957-a6e607c700e4 · outbound

This paper cites Ultralytics yolov8,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Ultralytics yolov8,

Reference 67

Resolution
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no resolver link, observed 2026-08-10T22:07:44.585871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.585871Z digest=sha256:142f9a3f929e99fc81695b841bddda537a4cb3d8bf52615821c5fbd567966b6e

Observation 12aab821-bf64-4eaa-a29b-982f952cf298 · outbound

This paper cites YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 68

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.589316Z digest=sha256:d5838798181a0463972a485368e8fe324ed8819cb761aacddba0a81d78adf37d

Observation ef867507-4475-4899-b3b9-1a53d7fa39b3 · outbound

This paper cites PP-YOLOE: An evolved version of YOLO.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification PP-YOLOE: An evolved version of YOLO

Reference 69

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no resolver link, observed 2026-08-10T22:07:44.593273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.593273Z digest=sha256:c84a1ecfb4592b148107a937deeb2fdfca73b5d08f68e3381b76ec228ef1787b

Observation 2ac30407-674e-41f0-a879-b43a5b942b2b · outbound

This paper cites Generalized focal loss: Towards efficient representation learning for dense object detec- tion,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Generalized focal loss: Towards efficient representation learning for dense object detec- tion,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.105937Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.601057Z digest=sha256:84fd0f87773ef964e6ec68c94dde183aae496bbfffd5971a940ba11bcdcfaf8d

Observation 0cda37d9-c102-4277-b0f5-e50c9d5fc482 · outbound

This paper cites Generalized intersection over union: A metric and a loss for bounding box regression,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Generalized intersection over union: A metric and a loss for bounding box regression,

Reference 72

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.604602Z digest=sha256:fbdee3e32240f731e65a4e6c0f5fe93de14218376d70b272aa7186efb4eb9024

Observation 5d61874c-af5e-4f39-8867-9c29a8d3d13c · outbound

This paper cites Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Bridging the gap between anchor-based and anchor-free detection via adaptive training sample selection,

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:07:44.607977Z digest=sha256:0eaeaee37f71f4dc111949ab91ac1f925a65f009642d177e9e8a2ac6620d3b54

Observation 97635347-4bbd-4d7d-8417-7973ed65c955 · outbound

This paper cites Ultralytics yolov8,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Ultralytics yolov8,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T22:07:46.076763Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-10T22:07:44.611487Z digest=sha256:4b18c27c2d0c2ad36629a8ab2c1021368c662776093d710274734d6f937e4424

Observation e82a210a-902b-4658-b8e9-fc025e0e1a4b · outbound

This paper cites YOLOX: Exceeding YOLO Series in 2021.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification YOLOX: Exceeding YOLO Series in 2021

Reference 75

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b690856e-4388-484d-84db-01c883e11ff1 · outbound

This paper cites Cracktinynet: A novel deep learning model specifically designed for superior performance in tiny road surface crack detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Cracktinynet: A novel deep learning model specifically designed for superior performance in tiny road surface crack detection,

Reference 76

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verified fuzzy
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Source-reported events for the cited work

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

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Observation 8fdad6c1-20d2-4511-9ce6-7ff470e876c1 · outbound

This paper cites Efficientdet: Scalable and efficient object detection,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Efficientdet: Scalable and efficient object detection,

Reference 77

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Source-reported events for the cited work

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Observation 17b7f57e-9cf0-46c6-80d6-569c2f2115ed · outbound

This paper cites ultralytics/yolov5: v6.2 - YOLOv5 Classification Models, Apple M1, Reproducibility, ClearML and Deci.ai integrations,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification ultralytics/yolov5: v6.2 - YOLOv5 Classification Models, Apple M1, Reproducibility, ClearML and Deci.ai integrations,

Reference 78

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 142d8496-e8ba-433d-af17-7a0fad499ec7 · outbound

This paper cites Ssd: Single shot multibox detector,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Ssd: Single shot multibox detector,

Reference 79

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Source-reported events for the cited work

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Observation ab62e387-e1db-4db5-853e-d076c01a84f0 · outbound

This paper cites YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification YOLOv6: A Single-Stage Object Detection Framework for Industrial Applications

Reference 80

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Source-reported events for the cited work

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Observation 579143c1-7f2f-45d1-b1ab-33c0158efc2f · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks,.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Faster r-cnn: Towards real-time object detection with region proposal networks,

Reference 87

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unresolved
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Source-reported events for the cited work

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Observation 98a2802c-e4bc-4244-bc6c-c4edde6cfa70 · outbound

This paper cites Available: http://dx.doi.org/10.1109/ICIP.2016.7533052.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: http://dx.doi.org/10.1109/ICIP.2016.7533052

Reference 2016

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unresolved
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Source-reported events for the cited work

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Observation 947c1dab-a2ad-4f93-a46f-93b1bb48833e · outbound

This paper cites Available: http://dx.doi.org/10.1111/mice.12297.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: http://dx.doi.org/10.1111/mice.12297

Reference 2017

Resolution
verified exact
doi, observed 2026-08-10T22:07:44.820331Z

Source-reported events for the cited work

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

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Observation c7fbc750-593a-44c2-b7fb-9f72ea838e22 · outbound

This paper cites Available: http://dx.doi.org/10.1016/j.autcon.2019.04.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: http://dx.doi.org/10.1016/j.autcon.2019.04

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.514081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5493bada-3819-43cc-800f-899e95925200 · outbound

This paper cites Available: http://dx.doi.org/10.1177/0361198120907283.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: http://dx.doi.org/10.1177/0361198120907283

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-10T22:07:44.480083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 792dc17d-f55c-4933-8de5-a31a9473d2bf · outbound

This paper cites Available: https://doi.org/10.5281/zenodo.7002879.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: https://doi.org/10.5281/zenodo.7002879

Reference 2022

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unresolved
no resolver link, observed 2026-08-10T22:07:44.633534Z

Source-reported events for the cited work

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Observation ad2a360c-43d5-4f00-939b-a66d654ee685 · outbound

This paper cites Available: https://ietresearch.onlinelibrary.wiley.com/ doi/abs/10.1049/itr2.12497.

RDD4D: 4D Attention-Guided Road Damage Detection And Classification Available: https://ietresearch.onlinelibrary.wiley.com/ doi/abs/10.1049/itr2.12497

Reference 2024

Resolution
verified exact
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Source-reported events for the cited work

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

No inbound Pith citation observations are available.