AIMC Topic: Pattern Recognition, Visual

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Atypical Asymmetry for Processing Human and Robot Faces in Autism Revealed by fNIRS.

PloS one
Deficits in the visual processing of faces in autism spectrum disorder (ASD) individuals may be due to atypical brain organization and function. Studies assessing asymmetric brain function in ASD individuals have suggested that facial processing, whi...

Extreme learning machine and adaptive sparse representation for image classification.

Neural networks : the official journal of the International Neural Network Society
Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks,...

Deep Neural Networks as a Computational Model for Human Shape Sensitivity.

PLoS computational biology
Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have larg...

Pattern recognition for electroencephalographic signals based on continuous neural networks.

Neural networks : the official journal of the International Neural Network Society
This study reports the design and implementation of a pattern recognition algorithm to classify electroencephalographic (EEG) signals based on artificial neural networks (NN) described by ordinary differential equations (ODEs). The training method fo...

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks.

NeuroImage
Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical proce...

Models of visual categorization.

Wiley interdisciplinary reviews. Cognitive science
Visual categorization refers to our ability to organize objects and visual scenes into discrete categories. It is an essential skill as it allows us to distinguish friend from foe or edible versus poisonous food. Understanding how the visual system c...

Atoms of recognition in human and computer vision.

Proceedings of the National Academy of Sciences of the United States of America
Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have s...

Effect of Subliminal Lexical Priming on the Subjective Perception of Images: A Machine Learning Approach.

PloS one
The purpose of the study is to examine the effect of subliminal priming in terms of the perception of images influenced by words with positive, negative, and neutral emotional content, through electroencephalograms (EEGs). Participants were instructe...

Multivoxel Object Representations in Adult Human Visual Cortex Are Flexible: An Associative Learning Study.

Journal of cognitive neuroscience
Learning associations between co-occurring events enables us to extract structure from our environment. Medial-temporal lobe structures are critical for associative learning. However, the role of the ventral visual pathway (VVP) in associative learni...