Predicting people’s daily activities with deep learning

A new study has found that applying deep learning on photos taken continuously from a wearable camera can predict human behaviours and may even help in the fight against chronic diseases. A team of researchers from Georgia Institute of Technology trained a convolutional neural network with a random decision forest, ‘late fusion ensemble’ (a classification method) on 40,103 photos from people’s daily activities over a six-month period to predict human behaviours. They published their results in a new paper, Predicting Daily Activities From Egocentric Images Using Deep Learning. The researchers say they expect this data to have applications in the healthcare industry as daily activities and lifestyle behaviours have strong links to the development of chronic diseases. Data was labelled into 19 categories such as chores, driving, cooking, exercising, reading,…

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