AIMC Topic: Neural Networks, Computer

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Convolutional neural network model by deep learning and teaching robot in keyboard musical instrument teaching.

PloS one
Keyboard instruments play a significant role in the music teaching process, providing students with an enjoyable musical experience while enhancing their music literacy. This study aims to investigate the current state of keyboard instrument teaching...

A machine learning approach for computation of cardiovascular intrinsic frequencies.

PloS one
Analysis of cardiovascular waveforms provides valuable clinical information about the state of health and disease. The intrinsic frequency (IF) method is a recently introduced framework that uses a single arterial pressure waveform to extract physiol...

Human-like systematic generalization through a meta-learning neural network.

Nature
The power of human language and thought arises from systematic compositionality-the algebraic ability to understand and produce novel combinations from known components. Fodor and Pylyshyn famously argued that artificial neural networks lack this cap...

Reduced-complexity Convolutional Neural Network in the compressed domain.

Neural networks : the official journal of the International Neural Network Society
Deep neural networks have achieved outstanding performance in computer vision tasks. Convolutional Neural Networks (CNNs) typically operate in the spatial domain with raw images, but in practice, images are usually stored and transmitted in their com...

DeepXplainer: An interpretable deep learning based approach for lung cancer detection using explainable artificial intelligence.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Artificial intelligence (AI) has several uses in the healthcare industry, some of which include healthcare management, medical forecasting, practical making of decisions, and diagnosis. AI technologies have reached human-lik...

Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization.

Scientific reports
In the past decade, there has been a sharp increase in publications describing applications of convolutional neural networks (CNNs) in medical image analysis. However, recent reviews have warned of the lack of reproducibility of most such studies, wh...

An advanced approach for the electrical responses of discrete fractional-order biophysical neural network models and their dynamical responses.

Scientific reports
The multiple activities of neurons frequently generate several spiking-bursting variations observed within the neurological mechanism. We show that a discrete fractional-order activated nerve cell framework incorporating a Caputo-type fractional diff...

Depressive Disorder Recognition Based on Frontal EEG Signals and Deep Learning.

Sensors (Basel, Switzerland)
Depressive disorder (DD) has become one of the most common mental diseases, seriously endangering both the affected person's psychological and physical health. Nowadays, a DD diagnosis mainly relies on the experience of clinical psychiatrists and sub...

Rapid automated 3-D pose estimation of larval zebrafish using a physical model-trained neural network.

PLoS computational biology
Quantitative ethology requires an accurate estimation of an organism's postural dynamics in three dimensions plus time. Technological progress over the last decade has made animal pose estimation in challenging scenarios possible with unprecedented d...

Discovery of type 2 diabetes mellitus with correlation and optimization driven hybrid deep learning approach.

Computer methods in biomechanics and biomedical engineering
Diabetes mellitus is a severe condition that has the potential to impair strength. The disease known as diabetes mellitus, which is a chronic condition, is brought on by a significant rise in blood glucose levels. The diagnosis of this condition is m...