AIMC Topic: Learning

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The neural representation of the gender of faces in the primate visual system: A computer modeling study.

Psychological review
We use an established neural network model of the primate visual system to show how neurons might learn to encode the gender of faces. The model consists of a hierarchy of 4 competitive neuronal layers with associatively modifiable feedforward synapt...

Training Feedforward Neural Networks Using Symbiotic Organisms Search Algorithm.

Computational intelligence and neuroscience
Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a chal...

What do we learn about development from baby robots?

Wiley interdisciplinary reviews. Cognitive science
Understanding infant development is one of the great scientific challenges of contemporary science. In addressing this challenge, robots have proven useful as they allow experimenters to model the developing brain and body and understand the processe...

Micro-Doppler Based Classification of Human Aquatic Activities via Transfer Learning of Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Accurate classification of human aquatic activities using radar has a variety of potential applications such as rescue operations and border patrols. Nevertheless, the classification of activities on using radar has not been extensively studied, unl...

A simplified computational memory model from information processing.

Scientific reports
This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracti...

Exponentially Long Orbits in Hopfield Neural Networks.

Neural computation
We show that Hopfield neural networks with synchronous dynamics and asymmetric weights admit stable orbits that form sequences of maximal length. For [Formula: see text] units, these sequences have length [Formula: see text]; that is, they cover the ...

Preschoolers Flexibly Adapt to Linguistic Input in a Noisy Channel.

Psychological science
Because linguistic communication is inherently noisy and uncertain, adult language comprehenders integrate bottom-up cues from speech perception with top-down expectations about what speakers are likely to say. Further, in line with the predictions o...

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

Journal of computational neuroscience
Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the unde...

A balanced motor primitive framework can simultaneously explain motor learning in unimanual and bimanual movements.

Neural networks : the official journal of the International Neural Network Society
Certain theoretical frameworks have successfully explained motor learning in either unimanual or bimanual movements. However, no single theoretical framework can comprehensively explain motor learning in both types of movement because the relationshi...

Neural network model develops border ownership representation through visually guided learning.

Neurobiology of learning and memory
As Rubin's famous vase demonstrates, our visual perception tends to assign luminance contrast borders to one or other of the adjacent image regions. Experimental evidence for the neuronal coding of such border-ownership in the primate visual system h...