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October 11, 2025Information Technology And ControlOpen Access

REWeather:A Unified Detection Framework for Automatic Driving Images Restoration and Enhancement in Adverse Weather

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Authors

XZXiaoyu ZhangXZXinyu ZhangXPXiting Peng

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Overview

Proposed framework improves detection accuracy in autonomous vehicles by 3.8%, indicating effective processing in adverse weather.

Key Points

  • Improved detection accuracy in autonomous vehicles enhances safety under adverse weather conditions.
  • Framework REWeather increases mAP by 3.8%, validating enhanced detection capabilities.
  • Utilizes Broad Learning System for classifying adverse weather types like fog, rain, and snow.
  • Employs Real-ESRGAN for detail enhancement and RT-DETR for effective object detection.

Cite This Study

Zhang et al. (2025) studied this question.

synapsesocial.com/papers/68ea72339f1bd4df558cedfbhttps://doi.org/10.5755/j01.itc.54.3.41307
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  1. 1Vehicle detection method in adverse weather conditions based on multitask deep learning2025 · 1 citations
  2. 2Real-Time Environment Condition Classification for Autonomous Vehicles2024
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  4. 4Weather-resilient Object Detection Framework for Autonomous Vehicles Using Conditional Preprocessing and YOLOv82026
  5. 5Degradation Type-Aware Image Restoration for Effective Object Detection in Adverse Weather2024 · 13 citations