scholarly journals THE IDENTIFICATION OF LATENT ATRIAL FIBRILLATION, DECREASED EJECTION FRACTION OF THE LEFT VENTRICLE AND POTASSIUM METABOLISM DISORDERS ON THE CONVENTIONAL ELECTROCARDIOGRAM USING DEEP CONVOLUTIONAL NEURAL NETWORK AS AN ELEMENT OF ARTIFICIAL INTELLIGENCE

2020 ◽  
pp. 193-193
Author(s):  
V.P. Mazaev ◽  
A.A. Komkov ◽  
S.V. Ryazanova ◽  
D.N. Samochatov ◽  
O.M. Drapkina
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Atrial Fibrillation ◽  
Left Ventricle ◽  
Ejection Fraction ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Potassium Metabolism

The impact of deep convolutional neural network‐based artificial intelligence on colonoscopy outcomes: A systematic review with meta‐analysis

2020 ◽  
Vol 35 (10) ◽  
pp. 1676-1683 ◽  
Author(s):  
Muhammad Aziz ◽  
Rawish Fatima ◽  
Charles Dong ◽  
Wade Lee‐Smith ◽  
Ali Nawras
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Systematic Review ◽  
Convolutional Neural Network ◽  
Meta Analysis ◽  
Deep Convolutional Neural Network ◽  
The Impact

scholarly journals Artificial intelligence in tongue diagnosis: Using deep convolutional neural network for recognizing unhealthy tongue with tooth-mark

2020 ◽  
Vol 18 ◽  
pp. 973-980
Author(s):  
Xu Wang ◽  
Jingwei Liu ◽  
Chaoyong Wu ◽  
Junhong Liu ◽  
Qianqian Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Tongue Diagnosis

scholarly journals Towards robotics and artificial intelligence for the prevention of Covid 19 pandemic

2021 ◽  
Vol 229 ◽  
pp. 01035
Author(s):  
Saloua Senhaji ◽  
Sanaa Faquir ◽  
Mohammed Ouazzani Jamil
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Train Station ◽  
Facial Mask ◽  
Corona Virus ◽  
Temperature Detection ◽  
Medical Crisis

In times of medical crisis, robotics and artificial intelligence helps humans manage emergencies and ensure a fast and efficient decontamination process. In this paper, we propose a robot with temperature detection, Corona virus checker using new biosensors, and artificial intelligence facial mask detection based on the deep convolutional neural network. Our robot can sterilize and patrol any type of area. In particular, airports, the train station and transport facilities which are the routes of transmission of the virus from one country to another.

Artificial intelligence classification of wetland vegetation morphology based on deep convolutional neural network

2019 ◽  
Vol 33 (1) ◽  
Author(s):  
Ping Lin ◽  
Qun Lu ◽  
Du Li ◽  
Yongming Chen ◽  
Zhiyong Zou ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Convolutional Neural Network ◽  
Wetland Vegetation ◽  
Deep Convolutional Neural Network

scholarly journals Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy – Artificial intelligence versus clinician for screening

2020 ◽  
Vol 68 (2) ◽  
pp. 398 ◽  
Author(s):  
Payal Shah ◽  
DivyanshK Mishra ◽  
MaheshP Shanmugam ◽  
Bindiya Doshi ◽  
Hariprasad Jayaraj ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Diabetic Retinopathy ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network

Acupoint Detection Based on Deep Convolutional Neural Network

2020 ◽  
Author(s):  
Lingyao Sun ◽  
Shiying Sun ◽  
Yuanbo Fu ◽  
Xiaoguang Zhao
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network

LENS CLASSIFICATION ACCORDING TO THE TYPE OF LIGHT SPOT USING A NEURAL NETWORK

2020 ◽  
Vol 2020 (4) ◽  
pp. 4-14
Author(s):  
Vladimir Budak ◽  
Ekaterina Ilyina
Keyword(s):  
Neural Network ◽  
Light Intensity ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Beam Angle ◽  
New Model ◽  
Technical Parameters ◽  
Transfer Training ◽  
Trained Network

The article proposes the classification of lenses with different symmetrical beam angles and offers a scale as a spot-light’s palette. A collection of spotlight’s images was created and classified according to the proposed scale. The analysis of 788 pcs of existing lenses and reflectors with different LEDs and COBs carried out, and the dependence of the axial light intensity from beam angle was obtained. A transfer training of new deep convolutional neural network (CNN) based on the pre-trained GoogleNet was performed using this collection. GradCAM analysis showed that the trained network correctly identifies the features of objects. This work allows us to classify arbitrary spotlights with an accuracy of about 80 %. Thus, light designer can determine the class of spotlight and corresponding type of lens with its technical parameters using this new model based on CCN.

Deep Convolutional Neural Network applied to Chagas Disease Parasitemia Assessment

2020 ◽  
Author(s):  
André Pereira ◽  
Alexandre Pyrrho ◽  
Daniel Vanzan ◽  
Leonardo Mazza ◽  
José Gabriel Gomes
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Chagas Disease ◽  
Deep Convolutional Neural Network

Estimating ambient visibility in the presence of fog: a deep convolutional neural network approach

2019 ◽  
Author(s):  
Fatma Outay ◽  
Bilal Taha ◽  
Hazar Chaabani ◽  
Faouzi Kamoun ◽  
Naoufel Werghi ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Convolutional Neural Network ◽  
Network Approach ◽  
Neural Network Approach
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