The Identification of Neurons Research

DOI

10.2991/iccia.2012.320How to use a DOI?

Keywords

neurons, L - Measure, Principal component analysis, Combined classifier, Recognition and classification

Abstract

In view of the present medical neurons characteristic cognition and human brain plan in the neurons of the limitation of recognition, this paper puts forward the neurons identification method. First the L - Measure software to neuron geometry feature extraction, and then to extract high dimensional feature through the principal component analysis dimension reduction processing. Combined classifier with pyramidal neurons, general Ken wild neurons, motor neuron, sensory neurons, double neurons, level 3 neurons and multistage neurons 7 kinds of neurons are classified. Experimental results prove that the probabilistic neural network, the BP neural network, fuzzy classifier composed of classifier recognition effect is superior to the arbitrary single classifier.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaojing Shang
PY  - 2014/05
DA  - 2014/05
TI  - The Identification of Neurons Research
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 1290
EP  - 1293
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.320
DO  - 10.2991/iccia.2012.320
ID  - Shang2014/05
ER  -