Paper Citation Record · LEDGER

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving

As of 20 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2506.02358.

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

pith.paper-citation-record.v1
2506.02358 v1

Coverage vector

measured 64 of 64 reference resolution

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measured 65 of 65 standing notices

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:51:40.200605Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:51:40.297133Z

Reference resolution

64 of 64 outbound references displayed

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External citation measurements

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Outbound references

Observation 11378110-4ed9-4e38-8dc3-baa51c7397df · outbound

This paper cites Speed-independent vibration-based terrain classification for passenger vehi- cles,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Speed-independent vibration-based terrain classification for passenger vehi- cles,

Reference 1

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Observation d205aba2-486b-4f90-ab1f-bf1dfc5f57f6 · outbound

This paper cites Road profile classification for vehicle semi-active suspension system based on adaptive neuro-fuzzy inference system,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Road profile classification for vehicle semi-active suspension system based on adaptive neuro-fuzzy inference system,

Reference 2

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Observation e9fd458b-a39e-49e9-a603-a9f19e999f56 · outbound

This paper cites Road segmen- tation for classification of road weather conditions,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Road segmen- tation for classification of road weather conditions,

Reference 3

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Observation f0435eee-3d7d-46d7-88e5-55de8fdbbc34 · outbound

This paper cites Evaluating features and classifiers for road weather condition anal- ysis,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Evaluating features and classifiers for road weather condition anal- ysis,

Reference 4

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Observation c69a7994-d8ca-4865-b45b-6840f75ec5c9 · outbound

This paper cites Road surface state recog- nition based on svm optimization and image segmen- tation processing,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Road surface state recog- nition based on svm optimization and image segmen- tation processing,

Reference 5

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Observation a1466bf5-5965-4f1f-808b-aa0f0244798b · outbound

This paper cites Estima- tion of tire-road peak adhesion coefficient for intelligent electric vehicles based on camera and tire dynamics information fusion,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Estima- tion of tire-road peak adhesion coefficient for intelligent electric vehicles based on camera and tire dynamics information fusion,

Reference 6

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Observation a1786662-274d-47fc-bcff-a6c36637e71a · outbound

This paper cites Prediction of vibrations as a measure of terrain traversability in outdoor structured and natural environments,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Prediction of vibrations as a measure of terrain traversability in outdoor structured and natural environments,

Reference 7

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Observation 680662a3-cd54-4b07-9b9c-2cae21f2f60d · outbound

This paper cites Kinetics of heal- ing of asphalt mixtures,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Kinetics of heal- ing of asphalt mixtures,

Reference 8

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Observation cd1ce33c-5b08-4979-a59d-879e6eea7462 · outbound

This paper cites A kinetics-based model of fatigue crack growth rate in bituminous material,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving A kinetics-based model of fatigue crack growth rate in bituminous material,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:45.930217Z

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Observation 7d9f324c-93a4-4413-8e7c-84e1b6f55335 · outbound

This paper cites Molecular dynamics investigation of interfacial adhe- sion between oxidised bitumen and mineral surfaces,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Molecular dynamics investigation of interfacial adhe- sion between oxidised bitumen and mineral surfaces,

Reference 10

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Observation 06013c55-af06-4d69-b082-d811e64191c4 · outbound

This paper cites Assessment of deep convolutional neural networks for road surface classification,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Assessment of deep convolutional neural networks for road surface classification,

Reference 11

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Observation fbd359fb-ade6-405d-bf2d-268f2ad521f7 · outbound

This paper cites Deep learning- based crack damage detection using convolutional neural networks,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Deep learning- based crack damage detection using convolutional neural networks,

Reference 12

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Observation 2a6b79b0-ce00-4c18-aac3-425e769bf40e · outbound

This paper cites Cross-scene pavement distress detection by a novel transfer learning framework,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Cross-scene pavement distress detection by a novel transfer learning framework,

Reference 13

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Observation 4de9fd75-f3e7-4d15-8259-cb3cf8acd3d9 · outbound

This paper cites Deep metric learning-based for multi-target few-shot pavement distress classification,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Deep metric learning-based for multi-target few-shot pavement distress classification,

Reference 14

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Observation bf303097-30be-4408-8707-6389a15c0528 · outbound

This paper cites HeightFormer: Learning Height Prediction in Voxel Features for Roadside Vision Centric 3D Object Detection via Transformer.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving HeightFormer: Learning Height Prediction in Voxel Features for Roadside Vision Centric 3D Object Detection via Transformer

Reference 15

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Observation 3cd1f482-e130-4a6c-a225-7c9ce1c22b0b · outbound

This paper cites Pavement anomaly detec- tion based on transformer and self-supervised learning,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Pavement anomaly detec- tion based on transformer and self-supervised learning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:45.815274Z

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Observation a55f8240-c33f-42b8-90ee-41feb1ad576f · outbound

This paper cites PillarMamba: Learning Local-Global Context for Roadside Point Cloud via Hybrid State Space Model.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving PillarMamba: Learning Local-Global Context for Roadside Point Cloud via Hybrid State Space Model

Reference 17

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Observation 4d799b49-2852-4a9c-99f7-9f88fddc003e · outbound

This paper cites Height3d: A roadside visual framework based on height prediction in real 3-d space,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Height3d: A roadside visual framework based on height prediction in real 3-d space,

Reference 18

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Observation bb5060c7-5af8-4221-bc93-c4a580976dc7 · outbound

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

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Gradient-based learning applied to document recogni- tion,

Reference 19

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Observation f0cbfcb3-0bf6-42bc-b64c-f4bb5175a98f · outbound

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

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Imagenet classification with deep convolutional neural networks,

Reference 20

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Observation e75da75f-a3d1-4594-908c-c805c440a0f0 · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 21

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This paper cites Going deeper with convolutions,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Going deeper with convolutions,

Reference 22

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This paper cites Deep residual learning for image recognition,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Deep residual learning for image recognition,

Reference 23

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Observation 37c9f5f3-eacf-483f-b2ac-a9c2bb467fe7 · outbound

This paper cites Densely connected convolutional networks,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Densely connected convolutional networks,

Reference 24

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This paper cites Squeeze-and-excitation networks,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Squeeze-and-excitation networks,

Reference 25

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Observation a1edd43d-d158-4d38-9da0-74e34209fe57 · outbound

This paper cites Winter Road Surface Condition Recognition Using A Pretrained Deep Convolutional Network.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Winter Road Surface Condition Recognition Using A Pretrained Deep Convolutional Network

Reference 26

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This paper cites Machine learning models for road surface and friction estimation using front-camera images,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Machine learning models for road surface and friction estimation using front-camera images,

Reference 27

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Observation cd978aec-3211-44bd-996d-a0229f0b80ca · outbound

This paper cites Road surface con- dition classification using deep learning,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Road surface con- dition classification using deep learning,

Reference 28

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This paper cites Rcnet: road clas- sification convolutional neural networks for intelligent vehicle system,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Rcnet: road clas- sification convolutional neural networks for intelligent vehicle system,

Reference 29

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This paper cites Design of Efficient Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Design of Efficient Deep Learning models for Determining Road Surface Condition from Roadside Camera Images and Weather Data

Reference 30

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Observation a63d63a2-7d06-4781-a9e3-a511ea0b2092 · outbound

This paper cites Rethinking the inception architecture for computer vision,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Rethinking the inception architecture for computer vision,

Reference 31

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This paper cites Xception: Deep learning with depthwise separable convolutions,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Xception: Deep learning with depthwise separable convolutions,

Reference 32

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This paper cites Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and seg- mentation,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Inverted residuals and linear bottlenecks: Mobile networks for classification, detection and seg- mentation,

Reference 33

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This paper cites Learning transferable architectures for scalable image recognition,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Learning transferable architectures for scalable image recognition,

Reference 34

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This paper cites Attention is all you need,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Attention is all you need,

Reference 35

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

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 36

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This paper cites Swin transformer: Hierarchical vi- sion transformer using shifted windows,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Swin transformer: Hierarchical vi- sion transformer using shifted windows,

Reference 37

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RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Swin transformer v2: Scaling up capacity and resolution,

Reference 38

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RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Deep learning with attention mechanisms for road weather detection,

Reference 39

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This paper cites Training data-efficient image transformers & distillation through attention,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Training data-efficient image transformers & distillation through attention,

Reference 40

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This paper cites Going deeper with image transformers,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Going deeper with image transformers,

Reference 41

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Observation bf0c96ed-d22b-42b6-a034-16f379fb294b · outbound

This paper cites Tokens-to-token vit: Training vision transformers from scratch on imagenet,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Tokens-to-token vit: Training vision transformers from scratch on imagenet,

Reference 42

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This paper cites Pyramid vision transformer: A versatile backbone for dense prediction without convo- lutions,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Pyramid vision transformer: A versatile backbone for dense prediction without convo- lutions,

Reference 43

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This paper cites Unext: Mlp- based rapid medical image segmentation network,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Unext: Mlp- based rapid medical image segmentation network,

Reference 44

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This paper cites Uformer: A general u-shaped transformer for image restoration,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Uformer: A general u-shaped transformer for image restoration,

Reference 45

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This paper cites U-net: Con- volutional networks for biomedical image segmenta- tion,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving U-net: Con- volutional networks for biomedical image segmenta- tion,

Reference 46

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This paper cites Cswin transformer: A general vi- sion transformer backbone with cross-shaped windows,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Cswin transformer: A general vi- sion transformer backbone with cross-shaped windows,

Reference 47

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Observation 2377853e-d169-473b-b0f4-c55d90ee455e · outbound

This paper cites HRFormer: High-Resolution Transformer for Dense Prediction.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving HRFormer: High-Resolution Transformer for Dense Prediction

Reference 48

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

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving End-to-end object detection with transformers,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:45.300031Z

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Observation 6bac0dda-9a0f-4204-956b-6f39b0d31844 · outbound

This paper cites Toward Transformer-Based Object Detection.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Toward Transformer-Based Object Detection

Reference 50

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Observation f0a33665-45b9-4920-8d35-1cfdded8b846 · outbound

This paper cites Conformer: Local features coupling global representations for visual recognition,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Conformer: Local features coupling global representations for visual recognition,

Reference 51

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Observation d5ea055e-9eb9-4aaf-b204-84a7c02bebe4 · outbound

This paper cites Mobile-former: Bridging mobilenet and trans- former,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Mobile-former: Bridging mobilenet and trans- former,

Reference 52

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This paper cites Early convolutions help transformers see better,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Early convolutions help transformers see better,

Reference 53

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Observation e99e742e-a5f6-45df-9cbb-e05bff0368dc · outbound

This paper cites LocalViT: Analyzing Locality in Vision Transformers.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving LocalViT: Analyzing Locality in Vision Transformers

Reference 54

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This paper cites Convit: Improving vision transformers with soft convolutional inductive biases,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Convit: Improving vision transformers with soft convolutional inductive biases,

Reference 55

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Observation 1ed5e79d-f63b-435e-9a1b-97ef6367db0a · outbound

This paper cites Picking deep filter responses for fine-grained image recognition,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Picking deep filter responses for fine-grained image recognition,

Reference 56

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This paper cites Learning multi- attention convolutional neural network for fine-grained image recognition,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Learning multi- attention convolutional neural network for fine-grained image recognition,

Reference 57

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This paper cites Subset feature learning for fine-grained category classification,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Subset feature learning for fine-grained category classification,

Reference 58

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Observation 6186bfc0-d825-45e5-a647-d90c2a881719 · outbound

This paper cites Multiple granularity descriptors for fine- grained categorization,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Multiple granularity descriptors for fine- grained categorization,

Reference 59

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Observation aa340b5d-a2bd-433f-9193-5a74cafc1e29 · outbound

This paper cites Are we ready for autonomous driving? the kitti vision benchmark suite,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving Are we ready for autonomous driving? the kitti vision benchmark suite,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:44.100293Z

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Observation b4ac8a91-b02a-4f7d-bffb-f31df0fe6c19 · outbound

This paper cites The cityscapes dataset for semantic urban scene un- derstanding,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving The cityscapes dataset for semantic urban scene un- derstanding,

Reference 61

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Observation ce055407-3349-4b96-a119-0db594232060 · outbound

This paper cites A compre- hensive implementation of road surface classification for vehicle driving assistance: Dataset, models, and deploy- ment,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving A compre- hensive implementation of road surface classification for vehicle driving assistance: Dataset, models, and deploy- ment,

Reference 62

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Observation 5bf1ed0c-6f8c-4611-a78f-b96215d28a02 · outbound

This paper cites A road surface image dataset with detailed annotations for driving assistance applications,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving A road surface image dataset with detailed annotations for driving assistance applications,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:43.678801Z

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Observation 1290701f-8b2d-48ec-a5b2-8ba3e81f0e55 · outbound

This paper cites A convnet for the 2020s,.

RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving A convnet for the 2020s,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T11:27:43.567601Z

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Pith citing papers

Observation 109c3824-c3ea-4682-8fb8-b85b5ee463ab · inbound

RoadMamba: A Dual Branch Visual State Space Model for Road Surface Classification cites this paper.

RoadMamba: A Dual Branch Visual State Space Model for Road Surface Classification RoadFormer : Local-Global Feature Fusion for Road Surface Classification in Autonomous Driving

Reference 24

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