AIMC Topic: Neurons

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Evolutionary Compression of Deep Neural Networks for Biomedical Image Segmentation.

IEEE transactions on neural networks and learning systems Sep 13, 2019
Biomedical image segmentation is lately dominated by deep neural networks (DNNs) due to their surpassing expert-level performance. However, the existing DNN models for biomedical image segmentation are generally highly parameterized, which severely i...
Humans Neural Networks, Computer Tomography, X-Ray Computed Data Compression Retinal Vessels Image Processing, Computer-Assisted Neurons
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Spiking Neural Networks and online learning: An overview and perspectives.

Neural networks : the official journal of the International Neural Network Society Sep 7, 2019
Applications that generate huge amounts of data in the form of fast streams are becoming increasingly prevalent, being therefore necessary to learn in an online manner. These conditions usually impose memory and processing time restrictions, and they...
Models, Neurological Action Potentials Algorithms Brain Neurons Education, Distance Humans Neural Networks, Computer
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Backpropagation With N -D Vector-Valued Neurons Using Arbitrary Bilinear Products.

IEEE transactions on neural networks and learning systems Sep 6, 2019
Vector-valued neural learning has emerged as a promising direction in deep learning recently. Traditionally, training data for neural networks (NNs) are formulated as a vector of scalars; however, its performance may not be optimal since associations...
Humans Neural Networks, Computer Support Vector Machine Deep Learning Neurons
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Machine learning applications in epilepsy.

Epilepsia Sep 3, 2019
Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recognition, lan...
Brain Electroencephalography Humans Deep Learning Seizures Signal Processing, Computer-Assisted Epilepsy Machine Learning Neurons
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The striatum specifies the statistics of behavior.

Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology Aug 29, 2019
Corpus Striatum Humans Machine Learning Neurons Animals Locomotion
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A null model of the mouse whole-neocortex micro-connectome.

Nature communications Aug 29, 2019
In connectomics, the study of the network structure of connected neurons, great advances are being made on two different scales: that of macro- and meso-scale connectomics, studying the connectivity between populations of neurons, and that of micro-s...
Neural Networks, Computer Animals Mice Brain Nerve Net Neocortex Models, Animal Models, Statistical Connectome Neurons
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Transformed ℓ regularization for learning sparse deep neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 27, 2019
Deep Neural Networks (DNNs) have achieved extraordinary success in numerous areas. However, DNNs often carry a large number of weight parameters, leading to the challenge of heavy memory and computation costs. Overfitting is another challenge for DNN...
Neurons Memory Neural Networks, Computer Machine Learning Algorithms
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A bioinspired optoelectronically engineered artificial neurorobotics device with sensorimotor functionalities.

Nature communications Aug 27, 2019
Development of the next generation of bio- and nano-electronics is inseparably connected to the innovative concept of emulation and reproduction of biological sensorimotor systems and artificial neurobotics. Here, we report for the first time princip...
Optogenetics Inhibitory Postsynaptic Potentials Electrical Synapses Muscles Electrochemical Techniques Bioengineering Neurons Metals, Heavy Robotics Alloys
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Locally connected spiking neural networks for unsupervised feature learning.

Neural networks : the official journal of the International Neural Network Society Aug 26, 2019
In recent years, spiking neural networks (SNNs) have demonstrated great success in completing various machine learning tasks. We introduce a method for learning image features with locally connected layers in SNNs using a spike-timing-dependent plast...
Neurons Neuronal Plasticity Neural Networks, Computer Models, Neurological Machine Learning
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Periodicity and finite-time periodic synchronization of discontinuous complex-valued neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 26, 2019
This paper discusses the issue of periodicity and finite-time periodic synchronization of discontinuous complex-valued neural networks (CVNNs). Based on a modified version of Kakutani's fixed point theorem, general conditions are obtained to guarante...
Neural Networks, Computer Algorithms Neurons Periodicity Feedback Time Factors
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