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Shrinking Bouma's window: Visual crowding in dense displays

Publications associées (44)

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Using the Neurorobotics platform to explain global processing in visual crowding

Michael Herzog, Gregory Francis, Alban Bornet

The Neurorobotics Platform of the Human Brain Project hosts many different large-scale models that can easily be connected with each other. Here, we linked a deep neural network for saliency computation to a spiking cortical model for visual segmentation ( ...

2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

Learning to embed data into a space where similar points are together and dissimilar points are far apart is a challenging machine learning problem. In this dissertation we study two learning scenarios that arise in the context of learning embeddings and o ...

EPFL2018

Towards goal-driven deep neural network models to elucidate human arm proprioception

Alexander Mathis, Matthias Bethge, Pranav Mamidanna

Proprioceptive signals are a critical component of our ability to perform complex movements, identify our posture and adapt to environmental changes. Our movements are generated by a large number of muscles and are sensed via a myriad of different receptor ...

2018

Learning embeddings: efficient algorithms and applications

Cijo Jose

École Polytechnique Fédérale de Lausanne2018

How grouping determines crowding

Michael Herzog

Crowding is traditionally thought to occur by local interactions between the target and the neighboring flankers, for example, by pooling neural responses corresponding to both the target and flankers. Accordingly, crowding is thought to occur within a sma ...

2017

EXPLOITING SEQUENCE INFORMATION FOR TEXT-DEPENDENT SPEAKER VERIFICATION

Petr Motlicek, Subhadeep Dey

Model-based approaches to Speaker Verification (SV), such as Joint Factor Analysis (JFA), i-vector and relevance Maximum-a-Posteriori (MAP), have shown to provide state-of-the-art performance for text-dependent systems with fixed phrases. The performance o ...

Ieee2017

Réseau de capteurs capacitifs pour la surveillance d'une occlusion dentaire

Marco Letizia, Marco Borotto

The invention relates to devices, systems and methods exploiting capacitive means for monitoring and analysing teeth-related parameters in a subject, such as the dental occlusion profile and/or the load/force applied upon clenching. The device comprises a ...

2017

Putting low-level vision into global context: Why vision cannot be reduced to basic circuits

Michael Herzog, Yvonne Evelina Thunell

To cope with the complexity of vision, most models in neuroscience and computer vision are of hierarchical and feedforward nature. Low-level vision, such as edge and motion detection, is explained by basic low-level neural circuits, whose outputs serve as ...

Elsevier2016

Adaptive data augmentation for image classification

Pascal Frossard, Alhussein Fawzi

Data augmentation is the process of generating samples by transforming training data, with the target of improving the accuracy and robustness of classifiers. In this paper, we propose a new automatic and adaptive algorithm for choosing the transformations ...

IEEE2016

The Honeycomb illusion: Uniform textures not perceived as such

Michael Herzog

We present a series of patterns, in which texture is perceived differently at fixation in comparison to the periphery, such that a physically uniform stimulus yields a nonuniform percept. We call this the Honeycomb illusion, and we discuss it in relation t ...

2016