Fuzzy and entropy facial recognition

08/24/2014
by   Jaejun Lee, et al.
0

This paper suggests an effective method for facial recognition using fuzzy theory and Shannon entropy. Combination of fuzzy theory and Shannon entropy eliminates the complication of other methods. Shannon entropy calculates the ratio of an element between faces, and fuzzy theory calculates the member ship of the entropy with 1. More details will be mentioned in Section 3. The learning performance is better than others as it is very simple, and only need two data per learning. By using factors that don't usually change during the life, the method will have a high accuracy.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
07/02/2018

Shannon entropy for intuitionistic fuzzy information

The paper presents an extension of Shannon fuzzy entropy for intuitionis...
research
02/25/2021

New identities for the Shannon function and applications

We show how the Shannon entropy function H(p,q)is expressible as a linea...
research
04/12/2021

Deep learning using Havrda-Charvat entropy for classification of pulmonary endomicroscopy

Pulmonary optical endomicroscopy (POE) is an imaging technology in real ...
research
11/19/2020

A Theory on AI Uncertainty Based on Rademacher Complexity and Shannon Entropy

In this paper, we present a theoretical discussion on AI deep learning n...
research
04/29/2020

To Reduce Gross NPA and Classify Defaulters Using Shannon Entropy

Non Performing Asset(NPA) has been in a serious attention by banks over ...
research
06/29/2023

Tokenization and the Noiseless Channel

Subword tokenization is a key part of many NLP pipelines. However, littl...
research
01/07/2018

Shannon Information Entropy in Heavy-ion Collisions

The general idea of information entropy provided by C.E. Shannon "hangs ...

Please sign up or login with your details

Forgot password? Click here to reset