AIMC Topic: Neural Networks, Computer

Clear Filters Showing 28411 to 28420 of 31376 articles

ARTIFICIAL NEURAL NETWORK MODELS FOR ESTIMATION OF ELECTRIC FIELD INTENSITY AND MAGNETIC FLUX DENSITY IN THE PROXIMITY OF OVERHEAD TRANSMISSION LINE.

Radiation protection dosimetry
This paper considers the application of artificial neural network (ANN) models for electric field intensity and magnetic flux density estimation in the proximity of overhead transmission lines. Specifically, two distinct ANN models are used to facili...

Temporal fact extraction of fruit cultivation technologies based on deep learning.

Mathematical biosciences and engineering : MBE
There are great differences in fruit planting techniques due to different regional environments. Farmers can't use the same standard in growing fruit. Most of the information about fruit planting comes from the Internet, which is characterized by com...

An introduction to machine learning for classification and prediction.

Family practice
Classification and prediction tasks are common in health research. With the increasing availability of vast health data repositories (e.g. electronic medical record databases) and advances in computing power, traditional statistical approaches are be...

Attention-guided multi-scale deep object detection framework for lymphocyte analysis in IHC histological images.

Microscopy (Oxford, England)
Tumor-infiltrating lymphocytes are specialized lymphocytes that can detect and kill cancerous cells. Their detection poses many challenges due to significant morphological variations, overlapping occurrence, artifact regions and high-class resemblanc...

A noise-robust deep clustering of biomolecular ions improves interpretability of mass spectrometric images.

Bioinformatics (Oxford, England)
MOTIVATION: Mass Spectrometry Imaging (MSI) analyzes complex biological samples such as tissues. It simultaneously characterizes the ions present in the tissue in the form of mass spectra, and the spatial distribution of the ions across the tissue in...

MFR-DTA: a multi-functional and robust model for predicting drug-target binding affinity and region.

Bioinformatics (Oxford, England)
MOTIVATION: Recently, deep learning has become the mainstream methodology for drug-target binding affinity prediction. However, two deficiencies of the existing methods restrict their practical applications. On the one hand, most existing methods ign...

AFTGAN: prediction of multi-type PPI based on attention free transformer and graph attention network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction (PPI) networks and transcriptional regulatory networks are critical in regulating cells and their signaling. A thorough understanding of PPIs can provide more insights into cellular physiology at normal and dis...

Deep Learning in Population Genetics.

Genome biology and evolution
Population genetics is transitioning into a data-driven discipline thanks to the availability of large-scale genomic data and the need to study increasingly complex evolutionary scenarios. With likelihood and Bayesian approaches becoming either intra...

Adversarial dense graph convolutional networks for single-cell classification.

Bioinformatics (Oxford, England)
MOTIVATION: In single-cell transcriptomics applications, effective identification of cell types in multicellular organisms and in-depth study of the relationships between genes has become one of the main goals of bioinformatics research. However, dat...

An Arbitrary Scale Super-Resolution Approach for 3D MR Images via Implicit Neural Representation.

IEEE journal of biomedical and health informatics
High Resolution (HR) medical images provide rich anatomical structure details to facilitate early and accurate diagnosis. In magnetic resonance imaging (MRI), restricted by hardware capacity, scan time, and patient cooperation ability, isotropic 3-di...