AIMC Topic: Neural Networks, Computer

Clear Filters Showing 20151 to 20160 of 31376 articles

Cross-Subject Seizure Detection in EEGs Using Deep Transfer Learning.

Computational and mathematical methods in medicine
Electroencephalography (EEG) plays an import role in monitoring the brain activities of patients with epilepsy and has been extensively used to diagnose epilepsy. Clinically reading tens or even hundreds of hours of EEG recordings is very time consum...

Training memristor-based multilayer neuromorphic networks with SGD, momentum and adaptive learning rates.

Neural networks : the official journal of the International Neural Network Society
Neural networks implemented with traditional hardware face inherent limitation of memory latency. Specifically, the processing units like GPUs, FPGAs, and customized ASICs, must wait for inputs to read from memory and outputs to write back. This moti...

Time-resolved correspondences between deep neural network layers and EEG measurements in object processing.

Vision research
The ventral visual stream is known to be organized hierarchically, where early visual areas processing simplistic features feed into higher visual areas processing more complex features. Hierarchical convolutional neural networks (CNNs) were largely ...

Generation and evaluation of synthetic patient data.

BMC medical research methodology
BACKGROUND: Machine learning (ML) has made a significant impact in medicine and cancer research; however, its impact in these areas has been undeniably slower and more limited than in other application domains. A major reason for this has been the la...

A Method to Extract Feature Variables Contributed in Nonlinear Machine Learning Prediction.

Methods of information in medicine
BACKGROUND: Although advances in prediction accuracy have been made with new machine learning methods, such as support vector machines and deep neural networks, these methods make nonlinear machine learning models and thus lack the ability to explain...

Assessing alternative methods for unsupervised segmentation of urban vegetation in very high-resolution multispectral aerial imagery.

PloS one
To analyze types and patterns of greening trends across a city, this study seeks to identify a method of creating very high-resolution urban vegetation maps that scales over space and time. Vegetation poses unique challenges for image segmentation be...

Acute and sub-acute stroke lesion segmentation from multimodal MRI.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Acute stroke lesion segmentation tasks are of great clinical interest as they can help doctors make better informed time-critical treatment decisions. Magnetic resonance imaging (MRI) is time demanding but can provide images...

Automatic snoring sounds detection from sleep sounds based on deep learning.

Physical and engineering sciences in medicine
Snoring is a typical characteristic of obstructive sleep apnea hypopnea syndrome (OSAHS) and can be used for its diagnosis. The purpose of this paper is to develop an automatic snoring detection algorithm for classifying snore and non-snore sound seg...

A Light-Weight Practical Framework for Feces Detection and Trait Recognition.

Sensors (Basel, Switzerland)
Fecal trait examinations are critical in the clinical diagnosis of digestive diseases, and they can effectively reveal various aspects regarding the health of the digestive system. An automatic feces detection and trait recognition system based on a ...

Multifaceted analysis of training and testing convolutional neural networks for protein secondary structure prediction.

PloS one
Protein secondary structure prediction remains a vital topic with broad applications. Due to lack of a widely accepted standard in secondary structure predictor evaluation, a fair comparison of predictors is challenging. A detailed examination of fac...