01897nam a22001577a 4500999001700000100007200017245007600089260002700165300000800192500125200200700004101452856003301493942001101526952010001537952010201637  c65481d65478  aShahani Imam Bux a12MSIT08aSupervisor - Dr. Sajida Parveen Soomro  aGender Classification Through Face Recognition Using MLP Neural Network  aNawabshahbQUESTc2019  a29p  aABSTRACT

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
be scaled out at same dimensions and same color. By using different dimensions of
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.
  aDepartment of Information Technology  uhttps://tinyurl.com/34yytswx  cTHESIS  00104070aRESEARCHbRESEARCHd2019-09-27l0oR/IMS-19pMP/46-534r2019-09-27 00:00:00yTHESIS  00104070aRESEARCHbRESEARCHd2023-12-18l0pMP/53-560r2023-12-18 00:00:00w2023-12-18yTHESIS