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Data · dataset · 2023

Saudi Arabia Public Roads Visual Pollution Dataset

Listed in Teesside University Research Data Repository

Visual Pollution (VP) is the visible deterioration and bad aesthetic quality of the natural and human-made landscapes.

Description

It also refers to the disruptive occurrence that limits the movability of the people on the public roads such as excavation barriers, potholes, and dilapidated sidewalks. The real VP dataset is collected from the kingdom of Saudi Arabia (KSA) regions via the Ministry of Municipal and Rural Affairs and Housing (MOMRAH) and used to develop the proposed deep learning framework.

If you are using this dataset for research purpose kindly cite the following papers: 1. Article Paper: "AlElaiwi, Mohammad, Mugahed A. Al-antari, Hafiz Farooq Ahmad, Areeba Azhar, Badar Almarri, and Jamil Hussain. "VPP: Visual Pollution Prediction Framework Based on a Deep Active Learning Approach Using Public Road Images." Mathematics 11, no. 1 (2022): 186." 2. Data Article: "AlElaiwi, M., Al-Antari, M. A., Ahmad, H. F., Azhar, A., Almarri, B., & Hussain, J. (2023).

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Visual pollution real images benchmark dataset on the public roads. Data in Brief, 50, 109491. doi.org/10.1016/j.dib.2023.109491" 3. Data repository itself: AlElaiwi, Mohammad; Ahmad, Hafiz; Hussain, Jamil; Al-antari, Mugahed; Almarri, Badar; Azhar, Areeba (2023), “Saudi Arabia Public Roads Visual Pollution Dataset ”, Mendeley Data, V3, doi: 10.17632/bb7b8vtwry.3

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Where it is published

Catalogue records · 1

Topics

From keywords
Artificial intelligence · Computer Science & AI · Computer vision · Deep learning · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Machine learning · Social Science
Inferred from text
Image 65%
Provenance · 1 source records, 16 field assertions
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