Results 31 to 40 of about 288,791 (262)

Sub-Millisecond Phase Retrieval for Phase-Diversity Wavefront Sensor

open access: yesSensors, 2020
We propose a convolutional neural network (CNN) based method, namely phase diversity convolutional neural network (PD-CNN) for the speed acceleration of phase-diversity wavefront sensing.
Yu Wu   +3 more
doaj   +1 more source

Convolutional neural networks: an overview and application in radiology

open access: yesInsights into Imaging, 2018
Convolutional neural network (CNN), a class of artificial neural networks that has become dominant in various computer vision tasks, is attracting interest across a variety of domains, including radiology.
Rikiya Yamashita   +3 more
doaj   +1 more source

Research on epileptic EEG recognition based on improved residual networks of 1-D CNN and indRNN

open access: yesBMC Medical Informatics and Decision Making, 2021
Background Epilepsy is one of the diseases of the nervous system, which has a large population in the world. Traditional diagnosis methods mostly depended on the professional neurologists’ reading of the electroencephalogram (EEG), which was time ...
Mengnan Ma   +4 more
doaj   +1 more source

Optimasi Convolutional Neural Network dan K-Fold Cross Validation pada Sistem Klasifikasi Glaukoma

open access: yesJurnal Elkomika, 2022
ABSTRAK Pada penelitian ini dilakukan perancangan arsitektur Convolutional Neural Network (CNN) yang terdiri dari 5 layer konvolusi dan 1-fully connected layer untuk mengklasifikasikan citra fundus kedalam kondisi normal, early, moderate, deep, dan ...
YUNENDAH NUR FUADAH   +5 more
doaj   +1 more source

SPEAKER IDENTIFICATION SYSTEM USING AUDIO SIGNAL AND DEEP LEARNING METHOD [PDF]

open access: yesProceedings on Engineering Sciences
Automatic Speaker Identification (ASI) does not result in high accuracy, so it is essential to develop a highly accurate Speaker Identification (SI) system. Artificial Intelligence has shown remarkable improvement in the development of such systems using
Neelam Nehra   +2 more
doaj   +1 more source

A lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images

open access: yesResults in Engineering
Brain tumor diagnosis requires precision due to the high mortality rate associated with the growth of abnormal cells in the brain. Early disease identification, improved survival rates, and less reliance on professional MRI analysis is possible with ...
Amreen Batool, Yung-Cheol Byun
doaj   +1 more source

Short Text Aspect-Based Sentiment Analysis Based on CNN + BiGRU

open access: yesApplied Sciences, 2022
This paper describes the construction a short-text aspect-based sentiment analysis method based on Convolutional Neural Network (CNN) and Bidirectional Gating Recurrent Unit (BiGRU).
Ziwen Gao   +3 more
doaj   +1 more source

Improved Handwritten Digit Recognition Using Convolutional Neural Networks (CNN) [PDF]

open access: yesSensors, 2020
Traditional systems of handwriting recognition have relied on handcrafted features and a large amount of prior knowledge. Training an Optical character recognition (OCR) system based on these prerequisites is a challenging task. Research in the handwriting recognition field is focused around deep learning techniques and has achieved breakthrough ...
Savita Ahlawat   +4 more
openaire   +3 more sources

Nondestructive prediction of physicochemical properties of kimchi sauce with artificial and convolutional neural networks

open access: yesInternational Journal of Food Properties, 2023
This study presents a comparison of prediction performances by an artificial neural network (ANN), well-known deep convolutional neural network (D-CNN) models, and four proposed shallow convolutional neural network (S-CNN) models to forecast three key ...
Hae-Il Yang   +8 more
doaj   +1 more source

SANet: Structure-Aware Network for Visual Tracking

open access: yes, 2017
Convolutional neural network (CNN) has drawn increasing interest in visual tracking owing to its powerfulness in feature extraction. Most existing CNN-based trackers treat tracking as a classification problem.
Fan, Heng, Ling, Haibin
core   +1 more source

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