Efficient LSTM parallelization on smartphone GPU
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Updated
Jun 7, 2017 - Java
Efficient LSTM parallelization on smartphone GPU
Fitness Monitor is an Android application that users can use to track their daily activities like walking, jogging, sitting, standing, walking upstairs and walking downstairs. The application uses a Convolutional Neural Network (CNN) to predict user activity automatically and stores the information in a database stored on the phone. The users ca…
MobiRNN code for the 1st International Workshop on Embedded and Mobile Deep Learning
SmartRelationship Android App
Sending mobile sensory data to a server as binary data
A context awareness framework for Android platform
Android application for reliable multidevice multisensor big data collection. This fork contains an extension proposed by @Giitto, @Mohaabenz, and @maherlaaroussi during their internship at @univ_spn.
An activity recognizer using a neural network implemented from scratch
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