Recognition of Fabric Structures Based on Improved Olfactory Neural Network

2010 ◽  
Author(s):  
Bao Xiaomin ◽  
Ni Xiaoqing ◽  
Wang Yaming ◽  
Zhou Yanjiang
Keyword(s):  
Neural Network ◽  
Olfactory Neural Network ◽  
Fabric Structures

Endonasal anatomy of the olfactory neural network: Surgical implications

2018 ◽  
Vol 128 (11) ◽  
pp. 2473-2477 ◽  
Author(s):  
Matias Gomez Galarce ◽  
Juan C. Yanez-Siller ◽  
Ricardo L. Carrau ◽  
Alaa Montaser ◽  
Lucas Ramos Lima ◽  
...  
Keyword(s):  
Neural Network ◽  
Olfactory Neural Network

OLFACTORY NEURAL NETWORK MODEL

1992 ◽  
Vol 06 (27) ◽  
pp. 1721-1728
Author(s):  
N. KAZAKOVA ◽  
VIK. DOTSENKO
Keyword(s):  
Neural Network ◽  
Phase Diagram ◽  
Mean Field ◽  
Hopfield Neural Network ◽  
Network System ◽  
Zero Temperature ◽  
Field Phase ◽  
Simple Generalization ◽  
Neural Network System ◽  
Olfactory Neural Network

A statistical neural network olfactory model is proposed. The model is a simple generalization of the Hopfield neural network system. Retrieval properties are analysed and the zero temperature mean field phase diagram is obtained.

Automatic Recognition Analysis of Fabric Structure Based on GLCM and BP Neural Network

2011 ◽  
Vol 332-334 ◽  
pp. 1167-1170
Author(s):  
Chang Sheng Zhang ◽  
Wei Ke ◽  
Guo He Wang
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Recognition Rate ◽  
Light Condition ◽  
Visual Measurement ◽  
Fabric Structure ◽  
Great Possibility ◽  
Occurrence Matrix ◽  
Fabric Structures ◽  
Very High

At present, the work to analyze fabric structure still depends on artificial visual measurement, which is easily influenced by personal sight, mood, mental state as well as light condition. With the development of image processing technology and artificial intelligence, automatic analysis on fabric structure as a replacement of manual labor is of great possibility. In this study, features of fabric-image have been extracted by GLCM (Gray Level Co-occurrence Matrix). These features were analyzed by employing a three layer BP neural network. Three kinds of fabric structures such as plain, twill and satin was verified and the accurate recognition rate is very high to 93.45%.

scholarly journals 2P230 Characterization of the olfactory neural network of the land slug using fluorescent voltage imaging(16. Neuronal circuit & Information processing,Poster)

2014 ◽  
Vol 54 (supplement1-2) ◽  
pp. S233
Author(s):  
Kohei Ishida ◽  
Tomoya Shimokawa ◽  
Yuuta Hamasaki ◽  
Yoshimasa Komatsuzaki ◽  
Satoshi Watanabe ◽  
...  
Keyword(s):  
Neural Network ◽  
Information Processing ◽  
Neuronal Circuit ◽  
Voltage Imaging ◽  
Olfactory Neural Network

scholarly journals Tea Classification Based on Artificial Olfaction Using Bionic Olfactory Neural Network

2006 ◽  
pp. 343-348 ◽  
Author(s):  
Xinling Yang ◽  
Jun Fu ◽  
Zhengguo Lou ◽  
Liyu Wang ◽  
Guang Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Olfactory Neural Network

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural
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