AIMC Topic:
Learning

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Artificial neuron-glia networks learning approach based on cooperative coevolution.

International journal of neural systems Feb 26, 2015
Artificial Neuron-Glia Networks (ANGNs) are a novel bio-inspired machine learning approach. They extend classical Artificial Neural Networks (ANNs) by incorporating recent findings and suppositions about the way information is processed by neural and...
Neuroglia Genetics Humans Neural Networks, Computer Algorithms Learning Neurons
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Effects of robotically modulating kinematic variability on motor skill learning and motivation.

Journal of neurophysiology Feb 11, 2015
It is unclear how the variability of kinematic errors experienced during motor training affects skill retention and motivation. We used force fields produced by a haptic robot to modulate the kinematic errors of 30 healthy adults during a period of p...
Young Adult Adult Sensitivity and Specificity Female Reproducibility of Results Motivation Pleasure Motor Skills Male Robotics Athletic Performance Humans Learning Golf
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Physics instruction induces changes in neural knowledge representation during successive stages of learning.

NeuroImage Feb 7, 2015
Incremental instruction on the workings of a set of mechanical systems induced a progression of changes in the neural representations of the systems. The neural representations of four mechanical systems were assessed before, during, and after three ...
Thinking Young Adult Adult Cerebral Cortex Male Comprehension Adolescent Magnetic Resonance Imaging Brain Mapping Machine Learning Learning Female Humans
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Attention modeled as information in learning multisensory integration.

Neural networks : the official journal of the International Neural Network Society Feb 2, 2015
Top-down cognitive processes affect the way bottom-up cross-sensory stimuli are integrated. In this paper, we therefore extend a successful previous neural network model of learning multisensory integration in the superior colliculus (SC) by top-down...
Animals Models, Neurological Attention Perception Humans Neural Networks, Computer Learning
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Training spiking neural models using artificial bee colony.

Computational intelligence and neuroscience Feb 1, 2015
Spiking neurons are models designed to simulate, in a realistic manner, the behavior of biological neurons. Recently, it has been proven that this type of neurons can be applied to solve pattern recognition problems with great efficiency. However, th...
Learning Neurons Neural Networks, Computer Algorithms Computer Simulation
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Connectionist perspectives on language learning, representation and processing.

Wiley interdisciplinary reviews. Cognitive science Jan 30, 2015
The field of formal linguistics was founded on the premise that language is mentally represented as a deterministic symbolic grammar. While this approach has captured many important characteristics of the world's languages, it has also led to a tende...
Speech Perception Reading Language Development Learning Neurons Humans Cognitive Science Neural Networks, Computer
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Scene recognition by manifold regularized deep learning architecture.

IEEE transactions on neural networks and learning systems Jan 22, 2015
Scene recognition is an important problem in the field of computer vision, because it helps to narrow the gap between the computer and the human beings on scene understanding. Semantic modeling is a popular technique used to fill the semantic gap in ...
Humans Neural Networks, Computer Algorithms Pattern Recognition, Visual Learning Pattern Recognition, Automated Photic Stimulation
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Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

IEEE transactions on neural networks and learning systems Jan 21, 2015
Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to ef...
Humans Biometric Identification Artificial Intelligence Pattern Recognition, Visual Information Storage and Retrieval Names Algorithms Face Learning Pattern Recognition, Automated
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Memristor-based multilayer neural networks with online gradient descent training.

IEEE transactions on neural networks and learning systems Jan 14, 2015
Learning in multilayer neural networks (MNNs) relies on continuous updating of large matrices of synaptic weights by local rules. Such locality can be exploited for massive parallelism when implementing MNNs in hardware. However, these update rules r...
Humans Neural Networks, Computer Algorithms Online Systems Signal Processing, Computer-Assisted Computer Simulation Neurons Learning Synapses
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Learning-regulated context relevant topographical map.

IEEE transactions on neural networks and learning systems Dec 24, 2014
Kohonen's self-organizing map (SOM) is used to map high-dimensional data into a low-dimensional representation (typically a 2-D or 3-D space) while preserving their topological characteristics. A major reason for its application is to be able to visu...
Humans Neural Networks, Computer Cluster Analysis Models, Neurological Neurons Algorithms Learning Time Factors
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