scholarly journals Deep neural network processing of DEER data

2018 ◽  
Vol 4 (8) ◽  
pp. eaat5218 ◽  
Author(s):  
Steven G. Worswick ◽  
James A. Spencer ◽  
Gunnar Jeschke ◽  
Ilya Kuprov
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Network Processing

scholarly journals Quantitative real-time pulse oximetry with ultrafast frequency-domain diffuse optics and deep neural network processing

2018 ◽  
Vol 9 (12) ◽  
pp. 5997 ◽  
Author(s):  
Yanyu Zhao ◽  
Mattew B. Applegate ◽  
Raeef Istfan ◽  
Ashvin Pande ◽  
Darren Roblyer
Keyword(s):  
Neural Network ◽  
Pulse Oximetry ◽  
Frequency Domain ◽  
Real Time ◽  
Deep Neural Network ◽  
Diffuse Optics ◽  
Time Pulse ◽  
Network Processing

Deep Neural Network Classification of I-123 Ioflupane SPECT

2020 ◽  
Author(s):  
David T. Wang ◽  
Brady Williamson ◽  
Thomas Eluvathingal ◽  
Bruce Mahoney ◽  
Jennifer Scheler
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Neural Network Classification

Method of determination of the text direction on the image with the use of convolutional neural network

2020 ◽  
pp. 96-99
Author(s):  
P.L. Nikolaev
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Deep Neural Network ◽  
Binary Classification ◽  
Synthetic Data ◽  
Real Data ◽  
Method Of Determination ◽  
Classification Of Images

This article deals with method of binary classification of images with small text on them Classification is based on the fact that the text can have 2 directions – it can be positioned horizontally and read from left to right or it can be turned 180 degrees so the image must be rotated to read the sign. This type of text can be found on the covers of a variety of books, so in case of recognizing the covers, it is necessary first to determine the direction of the text before we will directly recognize it. The article suggests the development of a deep neural network for determination of the text position in the context of book covers recognizing. The results of training and testing of a convolutional neural network on synthetic data as well as the examples of the network functioning on the real data are presented.

Sign in / Sign up

Export Citation Format

Share Document