Crowding and the Architecture of the Visual System
Graph Chatbot
Chat with Graph Search
Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.
DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.
The use of spaceborne medium resolution imaging spectrometers with neural network algorithms has proven a large potential for application with optically complex inland waters. We make use of this approach to investigate the bio-physical dynamics in a eutro ...
We show how nonlinear embedding algorithms popular for use with "shallow" semi-supervised learning techniques such as kernel methods can be easily applied to deep multi-layer architectures, either as a regularizer at the output layer, or on each layer of t ...
Automatic recognition of gestures using computer vision is important for many real-world applications such as sign language recognition and human-robot interaction (HRI). Our goal is a real-time hand gesture-based HRI interface for mobile robots. We use a ...
In crowding, perception of a target is strongly deteriorated by nearby elements. Crowding is often explained by pooling models predicting that adding flankers increases crowding. In contrast, the centroid hypothesis proposes that adding flankers decreases ...
Association for Research in Vision and Ophthalmology2012
Attention is crucial for visual perception because it allows the visual system to effectively use its limited resources by selecting behaviorally and cognitively relevant stimuli from the large amount of information impinging on the eyes. Reflexive, stimul ...
In classical models of vision, low level visual tasks are explained by low level neural mechanisms. For example, in crowding, perception of a target is impeded by nearby elements because, as it is argued, responses of neurons coding for nearby elements are ...
We address the problem of learning a classifier from distributed data over a number of arbitrarily connected machines without exchange of the datapoints. Our purpose is to train a neural network at each machine as if the entire dataset was locally availabl ...
Constructing and updating an internal model of verticality is fundamental for maintaining an erect posture and facilitating visuo-spatial processing. The judgment of the visual vertical (VV) has been intensively studied in psychophysical investigations and ...
Most models of vision focus either on the spatial or temporal aspects of visual processing and neglect the other component. A variety of studies have shown, however, that spatial and temporal processing cannot easily be separated. The shine-through effect ...
This paper extends prior work using Compositional Pattern Producing Networks (CPPNs) as a generative encoding for the purpose of simultaneously evolving robot morphology and control. A method is presented for translating CPPNs into complete robots includin ...