Concept

Market segmentation

Related publications (170)

The Little W-Net That Could: State-of-the-Art Retinal Vessel Segmentation with Minimalistic Models

The segmentation of the retinal vasculature from eye fundus images represents one of the most fundamental tasks in retinal image analysis. Over recent years, increasingly complex approaches based on sophisticated Convolutional Neural Network architectures ...

2020

An objective comparison of detection and segmentation algorithms for artefacts in clinical endoscopy

Georges Wagnières, Xiaokang Wang, Sharib Ali

We present a comprehensive analysis of the submissions to the first edition of the Endoscopy Artefact Detection challenge (EAD). Using crowd-sourcing, this initiative is a step towards understanding the limitations of existing state-of-the-art computer vis ...

NATURE PUBLISHING GROUP2020

Capsule networks as recurrent models of grouping and segmentation

Michael Herzog, Adrien Christophe Doerig, Bilge Sayim, Mauro Manassi, Lynn Schmittwilken

Classically, visual processing is described as a cascade of local feedforward computations. Feedforward Convolutional Neural Networks (ffCNNs) have shown how powerful such models can be. However, using visual crowding as a well-controlled challenge, we pre ...

2020

Frictional Intermediation in Over-the-Counter Markets

Julien Hugonnier

We extend Duffie et al.'s (2005) search-theoretic model of over-the-counter (OTC) asset markets, allowing for a decentralized inter-dealer market with arbitrary heterogeneity in dealers' valuations (or, equivalently, inventory costs). We develop a solution ...

OXFORD UNIV PRESS2020

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 ...

2020

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

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

Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets

Alexandre Terrier, Alain Farron, Elham Taghizadeh, Philippe Büchler

Objectives This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltration. M ...

SPRINGER2020

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

Pascal Frossard, Deniz Mercadier, 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

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