Capsule networks as recurrent models of grouping and segmentation
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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 ...
The currently best performing state-of-the-art saliency detection algorithms incorporate heuristic functions to evaluate saliency. They require parameter tuning, and the relationship between the parameter value and visual saliency is often not well underst ...
Experimentalists tend to classify models of visual perception as being either local or global, and involving either feedforward or feedback processing. We argue that these distinctions are not as helpful as they might appear, and we illustrate these issues ...
Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image long range depende ...
How the elements of a visual scene are grouped into objects is one of the most fundamental but still poorly understood questions in visual neuroscience. Most investigations of perceptual grouping focus on static stimuli, neglecting temporal aspects. Using ...
In this paper we give an overview of our work on an asynchronous BCI (where the subject makes self-paced decisions on when to switch from a mental task to the next) that responds every 1/2 second. A local neural classifier tries to recognize three differen ...
We present a data-driven approach to weighting the temporal context of signal energy to be used in a simple speech/non-speech detector (SND). The optimal weights are obtained using linear discriminant analysis (LDA). Regularization is performed to handle n ...
In spite of more than 100 years of research, the mechanisms underlying visual masking are still unknown. In recent publications, we introduced an unmasking paradigm involving the fusion of features that revealed interesting spatial characteristics. Here, w ...
This work investigates whether population vector coding, a distributed computational paradigm, could be a principle mechanism for performing sensorimotor and frames of reference transformations. This paper presents a multilayer neural network that can perf ...
Residual micro-saccades, tremor and fixation errors imply that, on different trials in visual tasks, stimulus arrays are inevitably presented at different positions on the retina. Positional variation is likely to be specially important for tasks involving ...