École Polytechnique Fédérale de Lausanne

About: École Polytechnique Fédérale de Lausanne is a facility organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Catalysis. The organization has 44041 authors who have published 98296 publications receiving 4372092 citations. The organization is also known as: EPFL & ETHL.

The blue brain project.

Abstract: Markram describes the impressive aims of the Blue Brain Project, in which the enormous computing power of IBM's Blue Gene supercomputer is being harnessed to build biologically accurate models of the neocortical column and, ultimately, the whole brain.

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

Abstract: This paper reviews the first challenge on single image super-resolution (restoration of rich details in an low resolution image) with focus on proposed solutions and results. A new DIVerse 2K resolution image dataset (DIV2K) was employed. The challenge had 6 competitions divided into 2 tracks with 3 magnification factors each. Track 1 employed the standard bicubic downscaling setup, while Track 2 had unknown downscaling operators (blur kernel and decimation) but learnable through low and high res train images. Each competition had ∽100 registered participants and 20 teams competed in the final testing phase. They gauge the state-of-the-art in single image super-resolution.

Double-Gate Tunnel FET With High- $\kappa$ Gate Dielectric

Abstract: In this paper, we propose and validate a novel design for a double-gate tunnel field-effect transistor (DG tunnel FET), for which the simulations show significant improvements compared with single-gate devices using a gate dielectric. For the first time, DG tunnel FET devices, which are using a high-gate dielectric, are explored using realistic design parameters, showing an on-current as high as 0.23 mA for a gate voltage of 1.8 V, an off-current of less than 1 fA (neglecting gate leakage), an improved average subthreshold swing of 57 mV/dec, and a minimum point slope of 11 mV/dec. The 2D nature of tunnel FET current flow is studied, demonstrating that the current is not confined to a channel at the gate-dielectric surface. When varying temperature, tunnel FETs with a high-kappa gate dielectric have a smaller threshold voltage shift than those using SiO2, while the subthreshold slope for fixed values of Vg remains nearly unchanged, in contrast with the traditional MOSFET. Moreover, an Ion/Ioff ratio of more than 2 times 1011 is shown for simulated devices with a gate length (over the intrinsic region) of 50 nm, which indicates that the tunnel FET is a promising candidate to achieve better-than-ITRS low-standby-power switch performance.

Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance

Abstract: We present a statistical view of the texture retrieval problem by combining the two related tasks, namely feature extraction (FE) and similarity measurement (SM), into a joint modeling and classification scheme. We show that using a consistent estimator of texture model parameters for the FE step followed by computing the Kullback-Leibler distance (KLD) between estimated models for the SM step is asymptotically optimal in term of retrieval error probability. The statistical scheme leads to a new wavelet-based texture retrieval method that is based on the accurate modeling of the marginal distribution of wavelet coefficients using generalized Gaussian density (GGD) and on the existence a closed form for the KLD between GGDs. The proposed method provides greater accuracy and flexibility in capturing texture information, while its simplified form has a close resemblance with the existing methods which uses energy distribution in the frequency domain to identify textures. Experimental results on a database of 640 texture images indicate that the new method significantly improves retrieval rates, e.g., from 65% to 77%, compared with traditional approaches, while it retains comparable levels of computational complexity.