Object Detection

Computer Vision Technique for locating instances of objects in images or videos

Object detection algorithms typically leverage machine learning or deep learning to produce meaningful results. When humans look at images or video, we can recognize and locate objects of interest within a matter of moments. The goal of object detection is to replicate this intelligence using a computer.

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Object Classification

To determine the class of each feature

The goal of object classification is to determine the class of each feature, such as a building. For example, you can use it to determine if a building is damaged after a natural disaster.

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Object Tracking

The ability to estimate or predict the position of a target object in each consecutive frame in video

Object tracking is a deep learning process where the algorithm tracks the movement of an object. In other words, it is the task of estimating or predicting the positions and other relevant information of moving objects in a video. Object tracking usually involves the process of object detection.

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Super Resolution

A class of techniques that enhance (increases) the resolution of an imaging system

Super-resolution imaging (SR) is a class of techniques that enhance (increase) the resolution of an imaging system. In optical SR the diffraction limit of systems is transcended, while in geometrical SR the resolution of digital imaging sensors is enhanced.

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Speed Estimation

The task of detecting and tracking vehicles whose real-world speeds are then estimated

The task is usually evaluated with recall and precision of the detected vehicle tracks as well as the mean or median errors of the estimated vehicle speeds.

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Analytics

The systemic computational analysis of data or statistics

It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also entails applying data patterns toward effective decision-making.

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