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Publications associées (28)

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TopoAL: An Adversarial Learning Approach for Topology-Aware Road Segmentation

Pascal Fua, Mateusz Kozinski, Leonardo Citraro, Subeesh Vasu

Most state-of-the-art approaches to road extraction from aerial images rely on a CNN trained to label road pixels as foreground and remainder of the image as background. The CNN is usually trained by minimizing pixel-wise losses, which is less than ideal t ...

2020

Slow Moving Capital and Trade Execution Costs: Evidence from a major trading Glitch

Pierre Collin-Dufresne, Vincent Jean Bogousslavsky

We investigate the impact of an exogenous trading glitch at a high-frequency market-making firm on standard measures of stock liquidity (spreads, price impact, turnover, and depth) and institutional trading costs (implementation shortfall and VWAP slippage ...

2021

Vision based pixel-level bridge structural damage detection using a link ASPP network

Wenlong Deng

Structural Health Monitoring (SHM) has greatly benefited from computer vision. Recently, deep learning approaches are widely used to accurately estimate the state of deterioration of infrastructure. In this work, we focus on the problem of bridge surface s ...

2020

Product assortment and space allocation strategies to attract loyal and non-loyal customers

Ralf Seifert, Anna Timonina-Farkas, Argyro Katsifou

Assortment planning deserves much attention from practitioners and academics due to its direct impact on retailers' commercial success. In this paper we focus on the increasingly popular retail practice to use combined product assortments with both "standa ...

2020

What are you synching about? Emerging complexity of Notch signaling in the segmentation clock

Andrew Charles Oates, Olivier François Venzin

The Segmentation clock is a population of cellular genetic oscillators, located in the posterior of the elongating vertebrate embryo, that governs the rhythmic and sequential segmentation of the body axis into somites. Somites are blocks of cells that give ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2020

Automatic Segmentation of Nuclei in Histopathology Images using Encoding-Decoding Convolutional Neural Networks

Pascal Frossard, Beril Besbinar

Accurate and fast segmentation of nuclei in histopathological images plays a crucial role in cancer research for detection and grading, as well as personal treatment. Despite the important efforts, current algorithms are still suboptimal in terms of speed, ...

IEEE2019

Learning to Reduce Annotation Load

Ksenia Konyushkova

Modern machine learning methods and their applications in computer vision are known to crave for large amounts of training data to reach their full potential. Because training data is mostly obtained through humans who manually label samples, it induces a ...

EPFL2019

Combined use of airborne laser scanning and hyperspectral imaging for forest inventories

Matthew Josef Parkan

The thesis presented hereby proposes as a general objective the estimation of forest inventory parameters (e.g. trunk location, height, basal area, crown area, species, etc..) from the combination of Airborne Laser Scanning (ALS) and Hyperspectal Imaging ( ...

EPFL2019