Results 51 to 60 of about 1,925,096 (328)

A Machine Learning Approach to Screen for Otitis Media Using Digital Otoscope Images Labelled by an Expert Panel

Diagnostics, 2022
Background: Otitis media includes several common inflammatory conditions of the middle ear that can have severe complications if left untreated. Correctly identifying otitis media can be difficult and a screening system supported by machine learning ...
Josefin Sandström, Hermanus Myburgh, Claude Laurent, De Wet Swanepoel, Thorbjörn Lundberg   +4 more
doaj   +1 more source

Three Dimensional Image Reconstruction of Electrical Capacitance Tomography Based on Improved ALEXNET Convolutional Neural Network

Journal of Harbin University of Science and Technology, 2020
A method is proposed that the corresponding AlexNet neural network is trained according to the data of different flow patterns for the problem of slow sample training and low imaging accuracy for the threedimensional image reconstruction algorithm of ...
LI Yan, WANG Lu, LI Jiaqi
doaj   +1 more source

Addressing Item-Cold Start Problem in Recommendation Systems using Model Based Approach and Deep Learning

, 2017
Traditional recommendation systems rely on past usage data in order to generate new recommendations. Those approaches fail to generate sensible recommendations for new users and items into the system due to missing information about their past ...
A Rajaraman, D Stojanovski, F Ricci, G Cormode, R Collobert   +4 more
core   +1 more source

Miners' facial expression recognition method based on convolutional neural network

Gong-kuang zidonghua, 2018
In view of problems of low recognition rate and complex algorithm of traditional miner's facial expression recognition methods, based on convolutional neural network and combining with nonlinear mapping function in support vector machine algorithm, a ...
DU Yun, ZHANG Lulu, PAN Tao
doaj   +1 more source

Dependency-based Convolutional Neural Networks for Sentence Embedding

, 2015
In sentence modeling and classification, convolutional neural network approaches have recently achieved state-of-the-art results, but all such efforts process word vectors sequentially and neglect long-distance dependencies. To exploit both deep learning
Huang, Liang, Ma, Mingbo, Xiang, Bing, Zhou, Bowen   +3 more
core   +1 more source

Lesion Location and Functional Connections Reveal Cognitive Impairment Networks in Multiple Sclerosis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive impairment, fatigue, and depression are common in multiple sclerosis (MS), potentially due to disruption of regional functional connectivity caused by white matter (WM) lesions. We explored whether WM lesions functionally connected to specific brain regions contribute to these MS‐related manifestations.
Alessandro Franceschini, Paolo Preziosa, Paola Valsasina, Damiano Mistri, Monica Margoni, Federica Esposito, Massimo Filippi, Maria A. Rocca   +7 more
wiley   +1 more source

Application of a Hybrid Model Based on a Convolutional Auto-Encoder and Convolutional Neural Network in Object-Oriented Remote Sensing Classification

Algorithms, 2018
Variation in the format and classification requirements for remote sensing data makes establishing a standard remote sensing sample dataset difficult. As a result, few remote sensing deep neural network models have been widely accepted.
Wei Cui, Qi Zhou, Zhendong Zheng
doaj   +1 more source

IMPLEMENTATION OF TECHNOLOGY FOR IMPROVING THE QUALITY OF SEGMENTATION OF MEDICAL IMAGES BY SOFTWARE ADJUSTMENT OF CONVOLUTIONAL NEURAL NETWORK HYPERPARAMETERS

Information and Telecommunication Sciences, 2023
Background. The scientists have built effective convolutional neural networks in their research, but the issue of optimal setting of the hyperparameters of these neural networks remains insufficiently researched.
Дмитро Прочухан
doaj   +1 more source

Learning to Detect Violent Videos using Convolutional Long Short-Term Memory

, 2017
Developing a technique for the automatic analysis of surveillance videos in order to identify the presence of violence is of broad interest. In this work, we propose a deep neural network for the purpose of recognizing violent videos.
Lanz, Oswald, Sudhakaran, Swathikiran
core   +1 more source

Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug‐Resistant Epilepsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To develop a novel deep‐learning model of clinical DWI tractography that can accurately predict the general assessment of epilepsy severity (GASE) in pediatric drug‐resistant epilepsy (DRE) and test if it can screen diverse neurocognitive impairments identified through neuropsychological assessments.
Jeong‐Won Jeong, Min‐Hee Lee, Hiroshi Uda, Yoon Ho Hwang, Michael Behen, Aimee Luat, Csaba Juhász, Eishi Asano   +7 more
wiley   +1 more source