This paper reviews the use of unmanned aerial vehicles (UAVs) for traffic monitoring, focusing on deep learning models for vehicle detection. While UAVs offer advantages like wide coverage and real-time data, challenges remain in processing high-resolution images, compensating for motion, and ensuring compatibility with existing intelligent transportation systems. Future research should address optimal detection models, edge processing, and integration with traffic control systems for improved responsiveness. AI
IMPACT Highlights the need for robust deep learning models and edge processing for real-time traffic management using UAVs.
RANK_REASON This is a review paper published on arXiv discussing experimental insights and future directions in a specific research area. [lever_c_demoted from research: ic=1 ai=1.0]
- alphaXiv
- arXiv
- CatalyzeX
- CORE Recommender
- DagsHub
- deep learning
- deep neural network
- Gotit.pub
- Hugging Face
- intelligent transportation system
- ScienceCast
- unmanned aerial vehicle
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