Automatic skin cancer detection and classification based on convolutional neural network and natural language processing

2021 ◽  
Author(s):  
Kewei Chen ◽  
Minghao Li ◽  
Zhimo Li ◽  
Yunpeng Tao
Keyword(s):  
Neural Network ◽  
Natural Language Processing ◽  
Skin Cancer ◽  
Natural Language ◽  
Convolutional Neural Network ◽  
Language Processing ◽  
Cancer Detection ◽  
Skin Cancer Detection

scholarly journals Epoch interrogation for skin cancer detection using convolutional neural network models

2021 ◽  
Vol 1074 (1) ◽  
pp. 012025
Author(s):  
A Poornima ◽  
M Shyamala Devi ◽  
M Sumithra ◽  
Mullaguri Venkata Bharath ◽  
Swathi ◽  
...  
Keyword(s):  
Neural Network ◽  
Skin Cancer ◽  
Convolutional Neural Network ◽  
Cancer Detection ◽  
Network Models ◽  
Neural Network Models ◽  
Skin Cancer Detection

scholarly journals Towards Accurate Deceptive Opinions Detection Based on Word Order-Preserving CNN

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Siyuan Zhao ◽  
Zhiwei Xu ◽  
Limin Liu ◽  
Mengjie Guo ◽  
Jing Yun
Keyword(s):  
Neural Network ◽  
Natural Language Processing ◽  
Natural Language ◽  
Convolutional Neural Network ◽  
Language Processing ◽  
Word Order ◽  
Text Analysis ◽  
Important Application ◽  
Detection Mechanism ◽  
Short Text

Convolutional neural network (CNN) has revolutionized the field of natural language processing, which is considerably efficient at semantics analysis that underlies difficult natural language processing problems in a variety of domains. The deceptive opinion detection is an important application of the existing CNN models. The detection mechanism based on CNN models has better self-adaptability and can effectively identify all kinds of deceptive opinions. Online opinions are quite short, varying in their types and content. In order to effectively identify deceptive opinions, we need to comprehensively study the characteristics of deceptive opinions and explore novel characteristics besides the textual semantics and emotional polarity that have been widely used in text analysis. In this paper, we optimize the convolutional neural network model by embedding the word order characteristics in its convolution layer and pooling layer, which makes convolutional neural network more suitable for short text classification and deceptive opinions detection. The TensorFlow-based experiments demonstrate that the proposed detection mechanism achieves more accurate deceptive opinion detection results.

scholarly journals Keratinocytic Skin Cancer Detection on the Face Using Region-Based Convolutional Neural Network

2020 ◽  
Vol 156 (1) ◽  
pp. 29 ◽  
Author(s):  
Seung Seog Han ◽  
Ik Jun Moon ◽  
Woohyung Lim ◽  
In Suck Suh ◽  
Sam Yong Lee ◽  
...  
Keyword(s):  
Neural Network ◽  
Skin Cancer ◽  
Convolutional Neural Network ◽  
Cancer Detection ◽  
The Face ◽  
Skin Cancer Detection
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