Vehicle Detection and Identification Using Artificial Intelligence Techniques
Keywords:
Detection, Identification, Occlusion, Tracking, Convolutional neural networksAbstract
This paper presents a model for detecting and identifying vehicles on public roads. To this end, it considers an artificial intelligence model based on the YOLO (You Only Look Once) model and the DeepSORT (Simple Online and
Realtime Tracking) algorithm. The resulting model was able to track vehicles in different situations of occlusions and variable environmental conditions. Once the vehicle was detected and identified, the model tracked it efficiently. As a result of the model's development, a dataset of vehicles commonly found on the streets of Argentina was created, containing 1,769 images labeled for the YOLO system. This work represents a proof of concept for generating new models with superior functionalities. The results show that the direction is appropriate.
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