International Journal of Advance Computational Engineering and Networking (IJACEN)
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Volume-12,Issue-9  ( Sep, 2024 )
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Feb. 2025
Submitted Papers : 80
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  Journal Paper


Paper Title :
Weather-Informed Vision Enhancement for Autonomous Vehicles in Adverse Conditions

Author :Emin Bayramov, Zoltan Istenes

Article Citation :Emin Bayramov ,Zoltan Istenes , (2024 ) " Weather-Informed Vision Enhancement for Autonomous Vehicles in Adverse Conditions " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 1-5, Volume-12,Issue-8

Abstract : Providing Advanced Driver Assistance Systems (ADAS) features requires high-quality image data collected by vehicles. However, adverse weather conditions and nighttime significantly degrade image quality, negatively impacting object detection accuracy and model performance for ADAS function- alities. This paper addresses this critical issue by referencing relevant works that have encountered similar challenges. We propose a novel solution that utilizes the vehicle’s GPS location and data collection timestamp to query weather forecast via a weather API. By obtaining precise weather details at the timeandlocationofdatacollection,weenhanceimagequalitythrough a pre-processing step tailored to the specific weather conditions. UsingtheDAWN(DetectioninAdverseWeatherNature)dataset, our approach demonstrates substantial improvements in image clarity and object detection accuracy across various weather scenarios, significantly enhancing the robustness and reliabilityof object detection models for ADAS systems. Keywords - ADAS Features, Image Enhancement, Adverse Weather Conditions, Object Detection, Weather Api

Type : Research paper

Published : Volume-12,Issue-8


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