scholarly journals GABOR FEATURE EXTRACTION DRIVEN FACIAL AGE ESTIMATION USING MULTILAYER PERCEPTRON NEURAL NETWORK

2020 ◽  
Vol 11 (3) ◽  
pp. 236-243
Author(s):  
Anjali A. Shejul ◽  
Kishor S. Kinage ◽  
Eswara Reddy B.
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Multilayer Perceptron ◽  
Age Estimation ◽  
Gabor Feature ◽  
Gabor Feature Extraction ◽  
Facial Age

scholarly journals Facial age estimation using SFTA and deep neural network

2018 ◽  
Vol 7 (2) ◽  
pp. 281
Author(s):  
Deepa Nagarajan ◽  
T. Sasipraba
Keyword(s):  
Neural Network ◽  
Feature Extraction ◽  
Age Estimation ◽  
Deep Neural Network ◽  
Age Groups ◽  
Histogram Equalization ◽  
Age Group ◽  
Final Layer ◽  
Feature Values ◽  
Facial Age

This paper construes the toils in facial age estimation in images. The fact that manual age estimation is indeed hard rising out the urge for digital age estimation. To make estimation precise many works have been carried out by considering a lot of constraints. In this paper, facial age estimation is done more accurately. SFTA method is used for feature extraction and meticulous results are obtained for all age groups. Histogram equalization is done using the Otsu algorithm and three layered Deep Neural Network is used to classify the age group. In a Deep neural network, softmax normalization is done in the final layer to preserve the outlier values. By extracting 45 feature values concerning color and gradient, key point descriptor, orientation, shape and texture better estimation are obtained.

Accelerating Multiresolution Gabor Feature Extraction for Real Time Vision Applications

2014 ◽  
Vol 76 (2) ◽  
pp. 149-168 ◽  
Author(s):  
Yong Cheol Peter Cho ◽  
Nandhini Chandramoorthy ◽  
Kevin M. Irick ◽  
Vijaykrishnan Narayanan
Keyword(s):  
Feature Extraction ◽  
Real Time ◽  
Gabor Feature ◽  
Gabor Feature Extraction

scholarly journals Face Recognition Based on Gabor Feature Extraction Followed by FastICA and LDA

2021 ◽  
Vol 68 (2) ◽  
pp. 1637-1659
Author(s):  
Masoud Muhammed Hassan ◽  
Haval Ismael Hussein ◽  
Adel Sabry Eesa ◽  
Ramadhan J. Mstafa
Keyword(s):  
Feature Extraction ◽  
Face Recognition ◽  
Gabor Feature ◽  
Gabor Feature Extraction

scholarly journals Pengenalan Angka Tulisan Tangan Menggunakan Diagonal Feature Extraction dan Artificial Neural Network Multilayer Perceptron

2018 ◽  
Vol 3 (1) ◽  
pp. 65
Author(s):  
M. Ardi Firmansyah ◽  
Kurniawan Nur Ramadhani ◽  
Anditya Arifianto
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Feature Extraction ◽  
Multilayer Perceptron ◽  
Artificial Neural

<p>Pada  penelitian  ini  dibangun  sistem pengenalan angka tulisan tangan menggunakan metode ekstraksi ciri diagonal  dan  Artificial Neural Network Multilayer Perceptron. Pada ekstraksi ciri diagonal, citra dibagi menjadi beberapa area yang sama besar. Pada tiap area dihitung rata-rata nilai piksel pada setiap diagonalnya kemudian dirata-ratakan untuk mendapatkan nilai ciri pada area tersebut.  Ciri diagonal dikombinasikan dengan nilai rata-rata horizontal dan  vertikal  pada  matriks  area  tersebut  untuk  memperkuat  informasi  pada citra. Metode  ini  mencapai  akurasi  sebesar  92.80%  pada  tahap  pengujian menggunakan  1000  dataset  C1  dan  92.60%  pada  tahap  pengujian  menggunakan 1000 dataset MNIST. Kombinasi fitur diagonal dan rata-rata horizontal menghasilkan akurasi tertinggi dalam mengenali angka tulisan tangan.</p>

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