Real-time embedded intelligence system : emotion recognition on Raspberry Pi with Intel NCS

Convolutional Neural Networks (CNNs) have exhibited certain human-like performance on computer vision related tasks. Over the past few years since they have outperformed conventional algorithms in a range of image processing problems. However, to utilise a CNN model with millions of free parameters on a source limited embedded system is a challenging problem. The Intel Neural Compute Stick (NCS) provides a possible route for running largescale neural networks on a low cost, low power, portable unit. In this paper, we propose a CNN based Raspberry Pi system that can run a pre-trained inference model in real time with an average power consumption of 6.2W. The Intel Movidius NCS, which avoids requirements of expensive processing units e.g. GPU, FPGA. The system is demonstrated using a facial image-based emotion recogniser. A fine-tuned CNN model is designed and trained to perform inference on each captured frame within the processing modules of NCS

Results from the ULTRA experiment in the framework of the EUSO project

The detection of Cerenkov light from EAS in a delayed coincidence with fluorescence light gives a strong signature to discriminate protons and neutrinos in cosmic rays. For this purpose, the ULTRA experiment has been designed with 2 detectors: a small EAS array (ETscope) and an UV optical device including wide field (Belenos) and narrow field (UVscope) Cerenkov light detectors. The array measures the shower size and the arrival direction of the incoming EAS, while the UV devices, pointing both to zenith and nadir, are used to determine the amount of direct and diffused coincident Cerenkov light. This information, provided for different diffusing surfaces, will be used to verify the possibility of detecting from Space the Cerenkov light produced by UHECRs with the EUSO experiment, on board the ISS

Proprietes vibrationnelles et conformationnelles de phosphazenes lineaires

SIGLEAvailable from INIST (FR), Document Supply Service, under shelf-number : T 77779 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

Extensive air showers and diffused Cherenkov light detection: The ULTRA experiment

The Uv Light Transmission and Reflection in the Atmosphere (ULTRA) experiment has been designed to provide quantitative measurements of the backscattered Cherenkov signal associated to the Extensive Air Showers (EAS) at the impact point on the Earth surface. The knowledge of such information will test the possibility to detect the diffused Cherenkov light spot from space within the Ultra high-energy cosmic ray observation. The Cherenkov signal is necessary to give an absolute reference for the track, allowing the measurement of the shower maximum and easing the separation between neutrino and hadronic showers. In this paper we discuss the experimental set-up with detailed information on the detection method; the in situ and laboratory calibrations; the simulation of the expected detector response and finally the preliminary results on the detector performance