Description: Object detection models are algorithms designed to identify and locate objects within images or videos. These models are fundamental in the field of computer vision and are used to recognize and classify different elements in a scene, providing not only the object’s category but also its exact position in terms of coordinates. Object detection relies on machine learning techniques, especially convolutional neural networks (CNNs), which allow models to learn complex visual features from large datasets. These models are particularly effective in various applications, integrating features from images to enhance detection accuracy and robustness. This ability to combine visual data enables models to better understand the context of an image or video, resulting in more precise object identification. The relevance of these models lies in their application across various fields, from security and surveillance to automotive and robotics, where accurate object detection is crucial for automated decision-making.
