Citation

Martin, Aerun and Kamaruddin, Mohd Nazeri and Md Sani, Zamani and Ab. Ghani, Hadhrami (2023) Enhancing Road Safety With ResNet: A Deep Learning Approach To Fog Removal In Road Images. In: 1st FET PG Engineering Colloquium Proceedings 2023, 16 June - 15 July 2023, Multimedia University, Malaysia. (Submitted)

Text 11_PPM Poster_CECI_Aerun_June2023.pdf Restricted to Registered users only Download (448kB)

Abstract

The study presents a ResNet-based dehazing algorithm for road images, outperforming existing techniques in PSNR and SSIM. It adapts to various haze patterns, removing haze while preserving scene details. The algorithm achieves an average PSNR of 28.29 and SSIM of 0.75, making it valuable for ADAS and autonomous vehicles.

Item Type:	Conference or Workshop Item (Poster)
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	15 Aug 2023 01:24
Last Modified:	15 Aug 2023 01:24
URII:	http://shdl.mmu.edu.my/id/eprint/11610

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