Indoor Actions Classification Through Long Short Term Memory Neural Networks
Conference paper
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Abstract
This work presents a system based on a recurrent deep neural network to classify actions performed in an indoor environment. RGBD and infrared sensors positioned in the rooms are used as data source. The smart environment the user lives in can be adapted to his/her needs.
Keywords
Deep learning Human actions LSTM Indoor activitiesReferences
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