AIMC Topic: Neural Networks, Computer

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Results of the 2023 ISBI challenge to reduce GABA-edited MRS acquisition time.

Magma (New York, N.Y.)
PURPOSE: Use a conference challenge format to compare machine learning-based gamma-aminobutyric acid (GABA)-edited magnetic resonance spectroscopy (MRS) reconstruction models using one-quarter of the transients typically acquired during a complete sc...

Bridges Between Spiking Neural Membrane Systems and Virus Machines.

International journal of neural systems
Spiking Neural P Systems (SNP) are well-established computing models that take inspiration from spikes between biological neurons; these models have been widely used for both theoretical studies and practical applications. Virus machines (VMs) are an...

Entropy-Weighted Numerical Gradient Optimization Spiking Neural System for Biped Robot Control.

International journal of neural systems
The optimization of robot controller parameters is a crucial task for enhancing robot performance, yet it often presents challenges due to the complexity of multi-objective, multi-dimensional multi-parameter optimization. This paper introduces a nove...

A neural network paradigm for modeling psychometric data and estimating IRT model parameters: Cross estimation network.

Behavior research methods
This paper presents a novel approach known as the cross estimation network (CEN) for fitting the datasets obtained from psychological or educational tests and estimating the parameters of item response theory (IRT) models. The CEN is comprised of two...

Mixing neural networks, continuation and symbolic computation to solve parametric systems of non linear equations.

Neural networks : the official journal of the International Neural Network Society
We consider a square non linear parametric equations system F(P,X) = 0 which is constituted of n non differential equations in the n unknowns {x,…,x} that are the components of X while P={p,…,p} is a set of m parameters that play a role in the defini...

A neurocomputational model of decision and confidence in object recognition task.

Neural networks : the official journal of the International Neural Network Society
How does the brain process natural visual stimuli to make a decision? Imagine driving through fog. An object looms ahead. What do you do? This decision requires not only identifying the object but also choosing an action based on your decision confid...

Modeling proprioception with task-driven neural network models.

Neuron
In a recent issue of Cell, Vargas and colleagues demonstrate that task-driven neural network models are superior at predicting proprioceptive activity in the primate cuneate nucleus and sensorimotor cortex compared with other models. This provides va...

A Multi-Modal Egocentric Activity Recognition Approach towards Video Domain Generalization.

Sensors (Basel, Switzerland)
Egocentric activity recognition is a prominent computer vision task that is based on the use of wearable cameras. Since egocentric videos are captured through the perspective of the person wearing the camera, her/his body motions severely complicate ...

Cardiac Arrhythmia Classification Using Advanced Deep Learning Techniques on Digitized ECG Datasets.

Sensors (Basel, Switzerland)
ECG classification or heartbeat classification is an extremely valuable tool in cardiology. Deep learning-based techniques for the analysis of ECG signals assist human experts in the timely diagnosis of cardiac diseases and help save precious lives. ...