Deep Learning on a Raspberry Pi for Real Time Face Recognition

I grew interested in trying to understand the American approach and the reasons behind the current American influence in medicine, and left The Norwegian University of Science

HRBF combines speed in the parameters computation with reconstruction accuracy and it is particularly suitable to be used with 3D digitisers to reconstruct in real-time a 3D

Recently, deep neu- ral networks and in particular convolutional neural net- works (CNNs) have shown impressive classification perfor- mance in face recognition tasks [TYRW14]..

In order to train a deep learning classifier with a sufficient amount of data, our emphasis was not on complete annotation of the slides but on finding enough candidates for

Whereas, the training policies of Double Deep Q-Learning, a Reinforcement Learning approach, enable the autonomous agent to learn effective navigation decisions form the

In this paper, we propose a new machine learning approach for target detection in radar, based solely on measured radar data.. By solely using measured radar data, we remove

It is the first version of the RCPSP where the aim is to select which tasks to complete (or leave undone) based on the utility value of tasks, while considering resources with

Fig 12 Error in range estimate as function of global error in sound speed Red solid curve: 10 km range 40 degrees off broadside Blue dotted line: 10 km range 10 degrees off