AIMC Topic: Neural Networks, Computer

Clear Filters Showing 12221 to 12230 of 31376 articles

A shallow deep learning approach to classify skin cancer using down-scaling method to minimize time and space complexity.

PloS one
The complex feature characteristics and low contrast of cancer lesions, a high degree of inter-class resemblance between malignant and benign lesions, and the presence of various artifacts including hairs make automated melanoma recognition in dermos...

A smoothing gradient-based neural network strategy for solving semidefinite programming problems.

Network (Bristol, England)
Linear semidefinite programming problems have received a lot of attentions because of large variety of applications. This paper deals with a smooth gradient neural network scheme for solving semidefinite programming problems. According to some proper...

Deep learning model to identify homonymous defects on automated perimetry.

The British journal of ophthalmology
BACKGROUND: Homonymous visual field (VF) defects are usually an indicator of serious intracranial pathology but may be subtle and difficult to detect. Artificial intelligence (AI) models could play a key role in simplifying the detection of these def...

Multimodal neural networks better explain multivoxel patterns in the hippocampus.

Neural networks : the official journal of the International Neural Network Society
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concept cells were discovered in a multimodal network called CLIP (Radford e...

Predicting H NMR acyl chain order parameters with graph neural networks.

Computational biology and chemistry
H NMR order parameters of the acyl chain of phospholipid membranes are an important indicator of the effects of molecules on membrane order, mobility, and permeability. So far, the evaluation procedures are case-by-case studies for every type of smal...

Assessment and Optimization of Explainable Machine Learning Models Applied to Transcriptomic Data.

Genomics, proteomics & bioinformatics
Explainable artificial intelligence aims to interpret how machine learning models make decisions, and many model explainers have been developed in the computer vision field. However, understanding of the applicability of these model explainers to bio...

Controlled Formation of Conduction Channels in Memristive Devices Observed by X-ray Multimodal Imaging.

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic computing provides a means for achieving faster and more energy efficient computations than conventional digital computers for artificial intelligence (AI). However, its current accuracy is generally less than the dominant software-based...

A hierarchy of linguistic predictions during natural language comprehension.

Proceedings of the National Academy of Sciences of the United States of America
Understanding spoken language requires transforming ambiguous acoustic streams into a hierarchy of representations, from phonemes to meaning. It has been suggested that the brain uses prediction to guide the interpretation of incoming input. However,...

Detection of Water pH Using Visible Near-Infrared Spectroscopy and One-Dimensional Convolutional Neural Network.

Sensors (Basel, Switzerland)
pH is an important parameter for water quality detection. This study proposed a novel calibration regression strategy based on a one-dimensional convolutional neural network (1D-CNN) for water pH detection using visible near-infrared (Vis-NIR) spectr...

Bearing Fault Diagnosis Using Lightweight and Robust One-Dimensional Convolution Neural Network in the Frequency Domain.

Sensors (Basel, Switzerland)
The massive environmental noise interference and insufficient effective sample degradation data of the intelligent fault diagnosis performance methods pose an extremely concerning issue. Realising the challenge of developing a facile and straightforw...