452 citations
- Institut des Matériaux Jean RouxelFR2 papers
- Nantes UniversitéFR2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- Fundacion Agencia Aragonesa para la Investigacion y el DesarrolloES1 paper
- General Mills (United States)US1 paper
- Instituto de Nanociencia y Materiales de AragónES1 paper
- Laboratoire des Sciences du Numérique de NantesFR1 paper
- Renishaw (United Kingdom)GB1 paper
- Universidad de ZaragozaES1 paper
- Zaragoza Logistics CenterES1 paper
6 papers
Coaxial nanowires as plasmon-mediated remote nanosensors
Daniel Funes-Hernando, Mario Pelaez-Fernandez, Dominik Winterauer +5
This study reports on the plasmon-mediated remote Raman sensing promoted by specially designed coaxial nanowires. This unusual geometry for Raman study is based on the separation,…
Sub-micron spatial resolution in far-field Raman imaging via positivity constrained super-resolution
Dominik J. Winterauer, Daniel Funes-Hernando, Jean-Luc Duvail +3
Raman microscopy is a valuable tool for detecting physical and chemical properties of a sample material. When probing nanomaterials or nanocomposites the spatial resolution of Rama…
SMASH: One-Shot Model Architecture Search through HyperNetworks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
Designing architectures for deep neural networks requires expert knowledge and substantial computation time. We propose a technique to accelerate architecture selection by learning…
FreezeOut: Accelerate Training by Progressively Freezing Layers
Andrew Brock, Theodore Lim, J. M. Ritchie +1
The early layers of a deep neural net have the fewest parameters, but take up the most computation. In this extended abstract, we propose to only train the hidden layers for a set…
Neural Photo Editing with Introspective Adversarial Networks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
The increasingly photorealistic sample quality of generative image models suggests their feasibility in applications beyond image generation. We present the Neural Photo Editor, an…
Generative and Discriminative Voxel Modeling with Convolutional Neural Networks
Andrew Brock, Theodore Lim, J. M. Ritchie +1
When working with three-dimensional data, choice of representation is key. We explore voxel-based models, and present evidence for the viability of voxellated representations in ap…