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Segun Adedipe

Data Scientist

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Human Activity Recognition

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About this project

This project aims to understand human behavior and assign a label to each action. It has a wide range of applications and therefore has been attracting increasing attention in the field of computer vision. Human actions can be represented using various data modalities, such as RGB, skeleton, depth, infrared, point cloud, event stream, audio, acceleration, radar, and WiFi signal, which encode different sources of useful yet distinct information and have various advantages depending on the application scenarios.

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