scispace - formally typeset
Search or ask a question
Institution

École Polytechnique Fédérale de Lausanne

FacilityLausanne, Switzerland
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.


Papers
More filters
Journal ArticleDOI
TL;DR: A high surface area pn-heterojunction between TiO2 and an organic p-type charge transport material (spiro-OMeTAD) was sensitized to visible light using lead sulfide (PbS) quantum dots as mentioned in this paper.
Abstract: A high surface area pn-heterojunction between TiO2 and an organic p-type charge transport material (spiro-OMeTAD) was sensitized to visible light using lead sulfide (PbS) quantum dots. PbS quantum dots were formed in situ on a nanocrystalline TiO2 electrode using chemical bath deposition techniques.1 The organic hole conductor was applied from solution to form the sensitized heterojunction. The structure of the quantum dots was analyzed using HRTEM technique. Ultrafast laser photolysis experiments suggested the initial charge separation to proceed in the subpicosecond time range. Transient absorption laser spectroscopy revealed that interfacial charge recombination of the initially formed charge carriers is much faster than in comparable dye-sensitized systems.2,3 The sensitized heterojunction showed incident photon-to-electron conversion efficiencies (IPCE) of up to 45% and energy conversion efficiencies under simulated sunlight AM1.5 (10 mW/cm2) of 0.49%.

749 citations

Journal ArticleDOI
TL;DR: In this article, an extension of the Minimal Standard Model by right-handed neutrinos (the νMSM) was proposed to incorporate neutrino masses consistent with oscillation experiments.

748 citations

Proceedings Article
21 Jun 2014
TL;DR: This work proposes an approach that consists of a recurrent convolutional neural network which allows us to consider a large input context while limiting the capacity of the model, and yields state-of-the-art performance on both the Stanford Background Dataset and the SIFT FlowDataset while remaining very fast at test time.
Abstract: The goal of the scene labeling task is to assign a class label to each pixel in an image. To ensure a good visual coherence and a high class accuracy, it is essential for a model to capture long range (pixel) label dependencies in images. In a feed-forward architecture, this can be achieved simply by considering a sufficiently large input context patch, around each pixel to be labeled. We propose an approach that consists of a recurrent convolutional neural network which allows us to consider a large input context while limiting the capacity of the model. Contrary to most standard approaches, our method does not rely on any segmentation technique nor any task-specific features. The system is trained in an end-to-end manner over raw pixels, and models complex spatial dependencies with low inference cost. As the context size increases with the built-in recurrence, the system identifies and corrects its own errors. Our approach yields state-of-the-art performance on both the Stanford Background Dataset and the SIFT Flow Dataset, while remaining very fast at test time.

747 citations

Journal ArticleDOI
TL;DR: The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community and it is the hope that winning entries may enhance the analysis methods of future BCIs.
Abstract: The BCI competition IV stands in the tradition of prior BCI competitions that aim to provide high quality neuroscientific data for open access to the scientific community. As experienced already in prior competitions not only scientists from the narrow field of BCI compete, but scholars with a broad variety of backgrounds and nationalities. They include high specialists as well as students. The goals of all BCI competitions have always been to challenge with respect to novel paradigms and complex data. We report on the following challenges: (1) asynchronous data, (2) synthetic, (3) multi-class continuous data, (4) session-to-session transfer, (5) directionally modulated MEG, (6) finger movements recorded by ECoG. As after past competitions, our hope is that winning entries may enhance the analysis methods of future BCIs.

747 citations

Journal ArticleDOI
01 Dec 2004
TL;DR: The AMON system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center, and is validated by a medical study with a set of 33 subjects.
Abstract: This paper describes an advanced care and alert portable telemedical monitor (AMON), a wearable medical monitoring and alert system targeting high-risk cardiac/respiratory patients. The system includes continuous collection and evaluation of multiple vital signs, intelligent multiparameter medical emergency detection, and a cellular connection to a medical center. By integrating the whole system in an unobtrusive, wrist-worn enclosure and applying aggressive low-power design techniques, continuous long-term monitoring can be performed without interfering with the patients' everyday activities and without restricting their mobility. In the first two and a half years of this EU IST sponsored project, the AMON consortium has designed, implemented, and tested the described wrist-worn device, a communication link, and a comprehensive medical center software package. The performance of the system has been validated by a medical study with a set of 33 subjects. The paper describes the main concepts behind the AMON system and presents details of the individual subsystems and solutions as well as the results of the medical validation.

747 citations


Authors

Showing all 44420 results

NameH-indexPapersCitations
Michael Grätzel2481423303599
Ruedi Aebersold182879141881
Eliezer Masliah170982127818
Richard H. Friend1691182140032
G. A. Cowan1592353172594
Ian A. Wilson15897198221
Johan Auwerx15865395779
Menachem Elimelech15754795285
A. Artamonov1501858119791
Melody A. Swartz1481304103753
Henry J. Snaith146511123155
Kurt Wüthrich143739103253
Richard S. J. Frackowiak142309100726
Jean-Paul Kneib13880589287
Kevin J. Tracey13856182791
Network Information
Related Institutions (5)
ETH Zurich
122.4K papers, 5.1M citations

98% related

Massachusetts Institute of Technology
268K papers, 18.2M citations

96% related

Georgia Institute of Technology
119K papers, 4.6M citations

96% related

Centre national de la recherche scientifique
382.4K papers, 13.6M citations

96% related

University of Illinois at Urbana–Champaign
225.1K papers, 10.1M citations

94% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023234
2022704
20215,249
20205,644
20195,432
20185,094