AIMC Topic: Neural Networks, Computer

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Agreement in Spiking Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology
We study the problem of binary agreement in a spiking neural network (SNN). We show that binary agreement on inputs can be achieved with of auxiliary neurons. Our simulation results suggest that agreement can be achieved in our network in time. We...

Prediction-error neurons in circuits with multiple neuron types: Formation, refinement, and functional implications.

Proceedings of the National Academy of Sciences of the United States of America
SignificanceAn influential idea in neuroscience is that neural circuits do not only passively process sensory information but rather actively compare them with predictions thereof. A core element of this comparison is prediction-error neurons, the ac...

General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
In this paper, we propose a unified and flexible framework for general image fusion tasks, including multi-exposure image fusion, multi-focus image fusion, infrared/visible image fusion, and multi-modality medical image fusion. Unlike other deep lear...

Detection of Highway Pavement Damage Based on a CNN Using Grayscale and HOG Features.

Sensors (Basel, Switzerland)
Aiming at the demand for rapid detection of highway pavement damage, many deep learning methods based on convolutional neural networks (CNNs) have been developed. However, CNN methods with raw image data require a high-performance hardware configurat...

Intrinsic bursts facilitate learning of Lévy flight movements in recurrent neural network models.

Scientific reports
Isolated spikes and bursts of spikes are thought to provide the two major modes of information coding by neurons. Bursts are known to be crucial for fundamental processes between neuron pairs, such as neuronal communications and synaptic plasticity. ...

Damage assessment in structures using artificial neural network working and a hybrid stochastic optimization.

Scientific reports
Artificial neural network (ANN) has been commonly used to deal with many problems. However, since this algorithm applies backpropagation algorithms based on gradient descent (GD) technique to look for the best solution, the network may face major ris...

An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction.

Scientific reports
Precise prediction of water quality parameters plays a significant role in making an early alert of water pollution and making better decisions for the management of water resources. As one of the influential indicative parameters, electrical conduct...

Automated quality assessment of large digitised histology cohorts by artificial intelligence.

Scientific reports
Research using whole slide images (WSIs) of histopathology slides has increased exponentially over recent years. Glass slides from retrospective cohorts, some with patient follow-up data are digitised for the development and validation of artificial ...

Self-consistent determination of long-range electrostatics in neural network potentials.

Nature communications
Machine learning has the potential to revolutionize the field of molecular simulation through the development of efficient and accurate models of interatomic interactions. Neural networks can model interactions with the accuracy of quantum mechanics-...

Rotating neurons for all-analog implementation of cyclic reservoir computing.

Nature communications
Hardware implementation in resource-efficient reservoir computing is of great interest for neuromorphic engineering. Recently, various devices have been explored to implement hardware-based reservoirs. However, most studies were mainly focused on the...