AIMC Topic: Neural Networks, Computer

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Facial feature point recognition method for human motion image using GNN.

Mathematical biosciences and engineering : MBE
To address the problems of facial feature point recognition clarity and recognition efficiency in different human motion conditions, a facial feature point recognition method using Genetic Neural Network (GNN) algorithm was proposed. As the technical...

InDeep: 3D fully convolutional neural networks to assist in silico drug design on protein-protein interactions.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interactions (PPIs) are key elements in numerous biological pathways and the subject of a growing number of drug discovery projects including against infectious diseases. Designing drugs on PPI targets remains a difficult ...

Virtifier: a deep learning-based identifier for viral sequences from metagenomes.

Bioinformatics (Oxford, England)
MOTIVATION: Viruses, the most abundant biological entities on earth, are important components of microbial communities, and as major human pathogens, they are responsible for human mortality and morbidity. The identification of viral sequences from m...

Automated classification of cytogenetic abnormalities in hematolymphoid neoplasms.

Bioinformatics (Oxford, England)
MOTIVATION: Algorithms for classifying chromosomes, like convolutional deep neural networks (CNNs), show promise to augment cytogeneticists' workflows; however, a critical limitation is their inability to accurately classify various structural chromo...

Detecting spatially co-expressed gene clusters with functional coherence by graph-regularized convolutional neural network.

Bioinformatics (Oxford, England)
MOTIVATION: Clustering spatial-resolved gene expression is an essential analysis to reveal gene activities in the underlying morphological context by their functional roles. However, conventional clustering analysis does not consider gene expression ...

Estimating vocal tract geometry from acoustic impedance using deep neural network.

JASA express letters
A data-driven approach using artificial neural networks is proposed to address the classic inverse area function problem, i.e., to determine the vocal tract geometry (modelled as a tube of nonuniform cylindrical cross-sections) from the vocal tract a...

Deep neural architectures for dialect classification with single frequency filtering and zero-time windowing feature representations.

The Journal of the Acoustical Society of America
The goal of this study is to investigate advanced signal processing approaches [single frequency filtering (SFF) and zero-time windowing (ZTW)] with modern deep neural networks (DNNs) [convolution neural networks (CNNs), temporal convolution neural n...

Coherent oscillations in balanced neural networks driven by endogenous fluctuations.

Chaos (Woodbury, N.Y.)
We present a detailed analysis of the dynamical regimes observed in a balanced network of identical quadratic integrate-and-fire neurons with sparse connectivity for homogeneous and heterogeneous in-degree distributions. Depending on the parameter va...

Understanding deep learning - challenges and prospects.

JPMA. The Journal of the Pakistan Medical Association
The developments in Artificial Intelligence have been on the rise since its advent. The advancements in this field have been the innovative research area across a wide range of industries, making its incorporation in dentistry inevitable. Artificial ...

All-day thin-lens computational imaging with scene-specific learning recovery.

Applied optics
Modern imaging optics ensures high-quality photography at the cost of a complex optical form factor that deviates from the portability. The drastic development of image processing algorithms, especially advanced neural networks, shows great promise t...