Fog-Aware Adaptive YOLO for Object Detection in Adverse Weather-Reference-Cited by-同舟云学术

Fog-Aware Adaptive YOLO for Object Detection in Adverse Weather

Published:2023-07-18 Issue: Volume: Page:
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Container-title:2023 IEEE Sensors Applications Symposium (SAS)
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Author:

Abbasi Hasan¹,Amini Marzieh¹,Yu F. Richard¹

Affiliation:

1. School of Information Technology, Carleton University,Ottawa,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10253663/10253664/10254059.pdf?arnumber=10254059

Reference19 articles.

1. Fog: Challenges and opportunities in autonomous vehicles;rashid;IEEE Transactions on Intelligent Transportation Systems,2021

2. Multi-level attention networks for robust object detection in adverse weather;fu;Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition,0

3. Adverse weather object detection based on fusion of visible and thermal images;lu;Journal of Physics Conference Series,0

4. Multi-sensor fusion for object detection in adverse weather conditions;qi;SENSORS,2019

5. Hierarchical feature aggregation for pedestrian detection in adverse weather;chen;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,0

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1. IDP-YOLOV9: Improvement of Object Detection Model in Severe Weather Scenarios from Drone Perspective;Applied Sciences;2024-06-18

2. Detection and performance analysis of vulnerable road users in low light conditions using YOLO;2024 10th International Conference on Communication and Signal Processing (ICCSP);2024-04-12

3. Comparative Analysis of mmWave Radar-based Object Detection in Autonomous Vehicles;2024 IEEE International Conference on Consumer Electronics (ICCE);2024-01-06