Gender Classification Through Face Recognition Using MLP Neural Network (Record no. 65481)

MARC details
000 -LEADER
fixed length control field 01676nam a22001337a 4500
100 ## - MAIN ENTRY--AUTHOR NAME
Personal name Shahani Imam Bux
-- 12MSIT08
-- Supervisor - Dr. Sajida Parveen Soomro
245 ## - TITLE STATEMENT
Title Gender Classification Through Face Recognition Using MLP Neural Network
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication Nawabshah
Name of publisher QUEST
Year of publication 2019
300 ## - PHYSICAL DESCRIPTION
Number of Pages 29p
500 ## - GENERAL NOTE
General note ABSTRACT<br/><br/>Artificial Neural Networks are playing vital role in machine learning. ANNs are also used for different fields of artificial intelligence. But it is most su itable for pattern recognition. Gender classification is an also prom ising area of Al i n which ANNs plays good role. ANNs also called Multi-Layer Perceptron (MLP), wh ich is widely used for pattern classification, recognition. Here MLP is used for gender classification with back propagation algorithm. MLP shows good resu lts when basic gender face image features are represented to it. This thesis work proposed a methodology for gender classification through face recognition by using MLP neu ral network. Training of MLP with male and female face images, the output are also categorized according to input images. For gender classification, face images should<br/>be scaled out at same dimensions and same color. By using different dimensions of<br/>face images with RGB color mode, the MLP gives good results up to 90%. Results are also altered when MLP attributes are changed. But it is tested that by using one hidden layer with 12 neurons generates good results. Some results are simulated through Neuroph Studio, a java based platform for neural network simulation.<br/>
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Department of Information Technology
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://tinyurl.com/34yytswx
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Thesis and Dissertation
Holdings
Withdrawn status Lost status Home library Current library Date acquired Full call number Accession Number Koha item type
    Research Section Research Section 27/09/2019 R/IMS-19 MP/46-534 Thesis and Dissertation
    Research Section Research Section 18/12/2023   MP/53-560 Thesis and Dissertation