RDD4D: 4D Attention-Guided Road Damage Detection And Classification | Paper Citation Record

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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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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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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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

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

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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

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

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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

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

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

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

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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

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

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

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

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

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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

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

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

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.361857Z

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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

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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

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

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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

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

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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

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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: verified fuzzy; 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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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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

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

Source-reported events for the cited work

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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

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:07:46.323613Z

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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

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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 2026-08-15T06:32:42.880941+00:00.

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

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

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

Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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

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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

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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

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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 2026-08-15T06:32:42.880941+00:00.

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

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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

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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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: verified exact; doi, observed 2026-08-10T22:07:44.761193Z

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.

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

Resolution: verified exact; doi, observed 2026-08-10T22:07:44.749464Z

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.

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

Resolution: verified exact; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: malformed identifier; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: verified fuzzy; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: verified exact; doi, observed 2026-08-10T22:07:44.720079Z

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.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.488077Z

Source-reported events for the cited work

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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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: verified fuzzy; 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.506340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: malformed identifier; no resolver link, observed 2026-08-10T22:07:44.517632Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.502870Z

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.524609Z

Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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

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

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.535208Z

Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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 2026-08-15T06:32:42.880941+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.554819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.562713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.570776Z

Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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

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

Source-reported events for the cited work

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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

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

Source-reported events for the cited work

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

Source-reported events for the cited work

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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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.589316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

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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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.604602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.607977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-15T06:32:42.880941+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.597247Z

Source-reported events for the cited work

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:07:46.062731Z

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.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.626017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; raw_fallback, observed 2026-08-10T22:07:46.040326Z

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.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.637099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.614997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.641660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-10T22:07:44.421288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-15T06:32:42.880941+00:00.

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.

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.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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; doi, observed 2026-08-10T22:07:44.682156Z

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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Reference resolution

Outbound references

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