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Comparative Evaluation of YOLO and Haar Cascade in Truck Detection in Road Scenarios in the City of Bogotá
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Resumen
This research paper focuses on the identification of objects using Neural Networks and Computer Vision in Python. The goal is to achieve high levels of performance and speed in object identification through database exploration, algorithm development using tools such as OpenCV, and research of specific mathematical models. A thorough search and selection of relevant databases was carried out to train and validate the Neural Network models used, resulting in high levels of accuracy and reliability in object identification.