This paper is published in Volume-5, Issue-4, 2019
Area
VLSI and Embedded Systems
Author
Shreyas Limaye
Co-authors
Dr. Virendra. V. Shete
Org/Univ
MIT College of Engineering, Pune, Maharashtra, India
Pub. Date
17 July, 2019
Paper ID
V5I4-1208
Publisher
Keywords
Deep learning, Expression recognition, CS-LBP

Citationsacebook

IEEE
Shreyas Limaye, Dr. Virendra. V. Shete. A facial-expression recognition model using deep learning, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Shreyas Limaye, Dr. Virendra. V. Shete (2019). A facial-expression recognition model using deep learning. International Journal of Advance Research, Ideas and Innovations in Technology, 5(4) www.IJARIIT.com.

MLA
Shreyas Limaye, Dr. Virendra. V. Shete. "A facial-expression recognition model using deep learning." International Journal of Advance Research, Ideas and Innovations in Technology 5.4 (2019). www.IJARIIT.com.

Abstract

Deep neural networks have been recently putting a breakthrough in pattern recognition, machine learning and artificial intelligence. This paper emphasizes a study based on deep learning framework contributing to the field of expression recognition. The proposed model involves a technique using deep for human facial expression recognition. Images are first preprocessed with normalization manipulation to remove illumination and facilitate enhancement using hat-filtering. At that point, a weighted, focus symmetric nearby paired example (CS-LBP) is connected to each face hinder by piece. The CS-LBP pieces are connected to form an element vector of the face picture. The deep network is trained using the layer-wise strategy. We use the CIFAR-10 dataset is used for training and testing. A database of real images is used for testing the algorithms. GUI has been created which compares trained and tested dataset and specifies the type of expression in the command window.
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