Vehicle Detection and Classification using YOLOv5 on Fused Infrared and Visible Images
Author:
Affiliation:
1. College of Engineering Thalassery, APJ Abdul Kalam Technological University,Kerala,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10133935/10133936/10134214.pdf?arnumber=10134214
Reference26 articles.
1. FlexiNet: Fast and Accurate Vehicle Detection for Autonomous Vehicles
2. Rapid Efficient Loss Less Color Image Compression Using RCT Technique and Hierarchical Prediction
3. Forward Vehicle Detection Based on Incremental Learning and Fast R-CNN
4. Vehicle detection using simplified fast R-CNN
5. Car Detection using Unmanned Aerial Vehicles: Comparison between Faster R-CNN and YOLOv3
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1. SBIT-Fuse: Infrared and visible image fusion based on Symmetrical Bilateral interaction and Transformer;Infrared Physics & Technology;2024-05
2. Traffic Surveillance System: Robust Multiclass Vehicle Detection and Classification;2024 5th International Conference on Advancements in Computational Sciences (ICACS);2024-02-19
3. Truck Detection and Counting in Low-Light Condition: Do We Need Infrared Camera?;2024 IEEE International Conference on Big Data and Smart Computing (BigComp);2024-02-18
4. A Nighttime Vehicle Detection Method Based on YOLO v8;2023 IEEE International Conference on Unmanned Systems (ICUS);2023-10-13
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