Classification of Chinese Herbal Medicines by deep neural network based on orthogonal design

2021 ◽  
Author(s):  
Yan Tang ◽  
Yan Wang ◽  
Jingzhong Li ◽  
Weiwei Zhang ◽  
Li Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Orthogonal Design ◽  
Herbal Medicines ◽  
Chinese Herbal Medicines ◽  
Chinese Herbal

Classification of Mixtures of Chinese Herbal Medicines Based on a Self-organizing Map (SOM)

2016 ◽  
Vol 35 (3-4) ◽  
pp. 109-115 ◽  
Author(s):  
Maolin Wang ◽  
Li Li ◽  
Changyuan Yu ◽  
Aixia Yan ◽  
Zhongzhen Zhao ◽  
...  
Keyword(s):  
Herbal Medicines ◽  
Self Organizing Map ◽  
Chinese Herbal Medicines ◽  
Chinese Herbal ◽  
Self Organizing

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.

Label-free non-invasive classification of rice seeds using optical coherence tomography assisted with deep neural network

2021 ◽  
Vol 137 ◽  
pp. 106861
Author(s):  
Deepa Joshi ◽  
Ankit Butola ◽  
Sheetal Raosaheb Kanade ◽  
Dilip K. Prasad ◽  
S.V. Amitha Mithra ◽  
...  
Keyword(s):  
Neural Network ◽  
Optical Coherence Tomography ◽  
Deep Neural Network ◽  
Optical Coherence ◽  
Label Free ◽  
Non Invasive ◽  
Rice Seeds
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