Printer Identification Using Supervised Learning for Document Forgery Detection

2014 ◽  
Author(s):  
Sara Elkasrawi ◽  
Faisal Shafait
Keyword(s):  
Supervised Learning ◽  
Forgery Detection

Supervised Learning-Based Feature Selection for Mondrian Paintings Style Authentication

2012 ◽  
Vol 16 (7) ◽  
pp. 894-899 ◽  
Author(s):  
Keon Myung Lee ◽  
◽  
Kyoung Soon Hwang ◽  
Kyung Mi Lee ◽  
Seung Kee Han ◽  
...  
Keyword(s):  
Feature Selection ◽  
Decision Tree ◽  
Supervised Learning ◽  
Computational Analysis ◽  
Learning Algorithms ◽  
Forgery Detection ◽  
Decision Tree Induction ◽  
Work Style ◽  
Supervised Learning Algorithms ◽  
Selection For

This paper concerns feature selection for computational analysis in authenticating works of art. The various features designed and extracted from art work in art forgery detection or the identification of the characteristics of art work style are valuable only when they have a meaningful influence on a given task such as classification. This paper presents features applicable to authenticating the painting style of Piet Mondrian and demonstrates meaningful features by using two supervised learning algorithms, a decision tree induction algorithm C4.5 and the Feature Generating Machine (FGM), both of which are used to select important features in the course of learning.

A Supervised Learning Approach for Dynamic Sampling (SLADS) in Raman Hyperspectral Imaging

2018 ◽  
Vol 2018 (15) ◽  
pp. 132-1-1323
Author(s):  
Shijie Zhang ◽  
Zhengtian Song ◽  
G. M. Dilshan P. Godaliyadda ◽  
Dong Hye Ye ◽  
Atanu Sengupta ◽  
...  
Keyword(s):  
Supervised Learning ◽  
Hyperspectral Imaging ◽  
Learning Approach ◽  
Dynamic Sampling
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