Object Detection & Recognition

Object detection and recognition is a fundamental problem in computer vision AI that involves identifying objects within an image or video and classifying them into predefined categories. This technology is widely used in a variety of applications, including self-driving cars, security systems, and retail analytics. Object detection and recognition involves using machine learning algorithms, such as convolutional neural networks (CNNs), to analyze visual data and make predictions about the objects within it.

Object detection and recognition in computer vision AI requires a large amount of data to train machine learning algorithms, as well as sophisticated algorithms that can accurately detect and classify objects. The process involves several steps, including object detection, object localization, and object recognition. These steps involve analyzing the visual data to identify regions of interest, extracting features from these regions, and using these features to classify objects. Overall, object detection and recognition is a critical technology in computer vision AI that has the potential to transform a wide range of industries.