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Pattern Recognition, Visual

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Perceptual dissociations among views of objects, scenes, and reachable spaces.

Journal of experimental psychology. Human perception and performance
In everyday experience, we interact with objects and we navigate through space. Extensive research has revealed that these visual behaviors are mediated by separable object-based and scene-based processing mechanisms in the mind and brain. However, w...

Emotional arousal amplifies competitions across goal-relevant representation: A neurocomputational framework.

Cognition
Emotional arousal often facilitates memory for some aspects of an event while impairing memory for other aspects of the same event. Across three experiments, we found that emotional arousal amplifies competition among goal-relevant representations, s...

Emergent neural turing machine and its visual navigation.

Neural networks : the official journal of the International Neural Network Society
Traditional Turing Machines (TMs) are symbolic whose hand-crafted representations are static and limited. Developmental Network 1 (DN-1) uses emergent representation to perform Turing Computation. But DN-1 lacks hierarchy in its internal representati...

System for Face Recognition under Different Facial Expressions Using a New Associative Hybrid Model Amαβ-KNN for People with Visual Impairment or Prosopagnosia.

Sensors (Basel, Switzerland)
Face recognition is a natural skill that a child performs from the first days of life; unfortunately, there are people with visual or neurological problems that prevent the individual from performing the process visually. This work describes a system...

Brain-inspired automated visual object discovery and detection.

Proceedings of the National Academy of Sciences of the United States of America
Despite significant recent progress, machine vision systems lag considerably behind their biological counterparts in performance, scalability, and robustness. A distinctive hallmark of the brain is its ability to automatically discover and model obje...

Figure-Ground Organization in Natural Scenes: Performance of a Recurrent Neural Model Compared with Neurons of Area V2.

eNeuro
A crucial step in understanding visual input is its organization into meaningful components, in particular object contours and partially occluded background structures. This requires that all contours are assigned to either the foreground or the back...

Reconstructing faces from fMRI patterns using deep generative neural networks.

Communications biology
Although distinct categories are reliably decoded from fMRI brain responses, it has proved more difficult to distinguish visually similar inputs, such as different faces. Here, we apply a recently developed deep learning system to reconstruct face im...

A fully convolutional two-stream fusion network for interactive image segmentation.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a novel fully convolutional two-stream fusion network (FCTSFN) for interactiveimage segmentation. The proposed network includes two sub-networks: a two-stream late fusion network (TSLFN) that predicts the foreground at a red...

Deep convolutional networks do not classify based on global object shape.

PLoS computational biology
Deep convolutional networks (DCNNs) are achieving previously unseen performance in object classification, raising questions about whether DCNNs operate similarly to human vision. In biological vision, shape is arguably the most important cue for reco...

Dense Associative Memory Is Robust to Adversarial Inputs.

Neural computation
Deep neural networks (DNNs) trained in a supervised way suffer from two known problems. First, the minima of the objective function used in learning correspond to data points (also known as rubbish examples or fooling images) that lack semantic simil...