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Data · dataset · 2023

Road Traversing Knowledge for Quality Classification

Listed in Teesside University Research Data Repository

This dataset consists of 6.297 labeled images from Brazil's inner country roads captured by a low-cost camera (HP Webcam HD-4110) attached to a moving vehicle.

Description

The dataset presents three quality levels classes (good, regular, and bad) for each surface kind: asphalt, paved and unpaved. The only exception is the unpaved surface that does not contain the class "good" due to its poor nature.

The number of images by surface-quality class is: asphalt-good: 1978 asphalt-regular: 839 asphalt-bad: 464 paved-good: 1179 paved-regular: 324 paved-bad: 124 unpaved_bad: 593 unpaved-regular: 796 All images were collected during the daytime in good weather conditions. The frames present lighting variations, shadows, and solar glare. Moreover, it is also noticed intra-class variations, such as asphalt surfaces with different color intensities, e.g., older asphalts are usually lighter than the new ones; paved surfaces formed by different patterns, e.g., cobblestone and concrete; and unpaved surfaces, which are naturally uneven.

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The directory is organized by subdirectories named with the "surface_quality".

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Where it is published

Catalogue records · 1

Topics

Inferred from text
Human geography 68% · Image 65%
Provenance · 1 source records, 12 field assertions
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Teesside University Research Data Repositoryoai:data.mendeley.com/ffwgjdfn86.110 d agoJSON v1
FieldAssertionExtractorEvidence
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concepts[field].local:field:social-sciencemapping · researchdata tees ac ukconnector:researchdata_tees_ac_uk@1.0.0
concepts[modality].local:modality:imageenrichment · researchdata tees ac ukkeyword-concept-rules@1.0.0title+description (65%)
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