Searching for low-mass dark matter particles with a massive Ge bolometer operated above-ground

no code implementations • 11 Jan 2019 • E. Armengaud, C. Augier, A. Benoît, A. Benoit, L. Bergé, J. Billard, A. Broniatowski, P. Camus, A. Cazes, M. Chapelier, F. Charlieux, D. Ducimetière, L. Dumoulin, K. Eitel, D. Filosofov, J. Gascon, A. Giuliani, M. Gros, M. De Jésus, Y. Jin, A. Juillard, M. Kleifges, R. Maisonobe, S. Marnieros, D. Misiak, X. -F. Navick, C. Nones, E. Olivieri, C. Oriol, P. Pari, B. Paul, D. Poda, E. Queguiner, S. Rozov, V. Sanglard, B. Siebenborn, L. Vagneron, M. Weber, E. Yakushev, A. Zolotarova, B. J. Kavanagh

The EDELWEISS collaboration has performed a search for dark matter particles with masses below the GeV-scale with a 33. 4-g germanium cryogenic detector operated in a surface lab.

Astrophysics of Galaxies Instrumentation and Methods for Astrophysics Instrumentation and Detectors

Deep learning for dehazing: Comparison and analysis

no code implementations • 28 Jun 2018 • A. Benoit, Leonel Cuevas, Jean-Baptiste Thomas

We compare a recent dehazing method based on deep learning, Dehazenet, with traditional state-of-the-art approaches , on benchmark data with reference.

Three dimensional Deep Learning approach for remote sensing image classification

no code implementations • 15 Jun 2018 • Amina Ben Hamida, A. Benoit, Patrick Lambert, Chokri Ben Amar

Recently, a variety of approaches has been enriching the field of Remote Sensing (RS) image processing and analysis.

Classification General Classification +3