AIMC Topic: Neurons

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Image Inpainting With Local and Global Refinement.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Mar 15, 2022
Image inpainting has made remarkable progress with recent advances in deep learning. Popular networks mainly follow an encoder-decoder architecture (sometimes with skip connections) and possess sufficiently large receptive field, i.e., larger than th...
Neurons Neural Networks, Computer Image Processing, Computer-Assisted
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Emergence of Direction-Selective Retinal Cell Types in Task-Optimized Deep Learning Models.

Journal of computational biology : a journal of computational molecular cell biology Mar 11, 2022
Convolutional neural networks (CNNs), a class of deep learning models, have experienced recent success in modeling sensory cortices and retinal circuits through optimizing performance on machine learning tasks, otherwise known as task optimization. P...
Neural Networks, Computer Machine Learning Neurons Retina Deep Learning
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Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning.

IEEE transactions on cybernetics Mar 11, 2022
Spikes are the currency in central nervous systems for information transmission and processing. They are also believed to play an essential role in low-power consumption of the biological systems, whose efficiency attracts increasing attentions to th...
Learning Neurons Neural Networks, Computer
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A behavioral paradigm for cortical control of a robotic actuator by freely moving rats in a one-dimensional two-target reaching task.

Journal of neuroscience methods Mar 7, 2022
BACKGROUND: Controlling the trajectory of a neuroprosthesis to reach distant targets is a commonly used brain-machine interface (BMI) task in primates and has not been available for rodents yet.
Rats Brain-Computer Interfaces Animals Movement Robotic Surgical Procedures Neurons Robotics Motor Cortex
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Synaptic Learning With Augmented Spikes.

IEEE transactions on neural networks and learning systems Feb 28, 2022
Traditional neuron models use analog values for information representation and computation, while all-or-nothing spikes are employed in the spiking ones. With a more brain-like processing paradigm, spiking neurons are more promising for improvements ...
Learning Action Potentials Neural Networks, Computer Recognition, Psychology Neurons
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Versatile memristor for memory and neuromorphic computing.

Nanoscale horizons Feb 28, 2022
The memristor is a promising candidate to implement high-density memory and neuromorphic computing. Based on the characteristic retention time, memristors are classified into volatile and non-volatile types. However, a single memristor generally prov...
Electronics Costs and Cost Analysis Synapses Neural Networks, Computer Neurons
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Broad Echo State Network with Reservoir Pruning for Nonstationary Time Series Prediction.

Computational intelligence and neuroscience Feb 27, 2022
The nonstationary time series is generated in various natural and man-made systems, of which the prediction is vital for advanced control and management. The neural networks have been explored in the time series prediction, but the problem remains in...
Time Factors Neurons Neural Networks, Computer Algorithms Humans
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A new automatic forecasting method based on a new input significancy test of a single multiplicative neuron model artificial neural network.

Network (Bristol, England) Feb 23, 2022
The model adequacy and input significance tests have not been proposed as features for the specification of a single multiplicative neuron model artificial neural networks in the literature. Moreover, there is no systematic approach based on hypothes...
Neural Networks, Computer Forecasting Algorithms Machine Learning Neurons
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Organic electrochemical neurons and synapses with ion mediated spiking.

Nature communications Feb 22, 2022
Future brain-machine interfaces, prosthetics, and intelligent soft robotics will require integrating artificial neuromorphic devices with biological systems. Due to their poor biocompatibility, circuit complexity, low energy efficiency, and operating...
Silicon Synapses Brain-Computer Interfaces Robotics Neurons Neuronal Plasticity
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Spatiotemporal dynamics in spiking recurrent neural networks using modified-full-FORCE on EEG signals.

Scientific reports Feb 21, 2022
Methods on modelling the human brain as a Complex System have increased remarkably in the literature as researchers seek to understand the underlying foundations behind cognition, behaviour, and perception. Computational methods, especially Graph The...
Behavior Humans Electroencephalography Brain Models, Neurological Neural Networks, Computer Cognition Perception Neurons
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