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Convolutional Neural Networks for Facial Expression Recognition

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Convolutional Neural Networks for Facial Expression Recognition


Rashmi Yadav | Mr. Ghanshyam Sahu | Lalitkumar P Bhaiya



Rashmi Yadav | Mr. Ghanshyam Sahu | Lalitkumar P Bhaiya "Convolutional Neural Networks for Facial Expression Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-8 | Issue-3, June 2024, pp.277-283, URL: https://www.ijtsrd.com/papers/ijtsrd64783.pdf

In the context of this study, convolutional neural networks (CNNs) have been developed with the objective of identifying facial expressions. The primary aim of this study project is to categorize each facial image into one of the seven distinct categories of facial expressions under investigation. The training of Convolutional Neural Network (CNN) models with different levels of depth included the use of grayscale photographs sourced from the Kaggle website [1]. By using Torch [2], we successfully developed our models and used the computational capabilities of Graphics Processing Units (GPUs) to enhance the efficiency of the training procedure. In addition, we used a hybrid feature method alongside the networks that were operating on raw pixel data. By integrating raw pixel data with Histogram of Oriented Gradients (HOG) characteristics, we were able to train a distinctive CNN model [3]. We used several techniques, including dropout and batch normalization, along with L2 regularization, to mitigate the occurrence of overfitting in the models. Cross-validation was used to determine the optimal hyper-parameters, and the performance of the generated models was assessed by examining their individual training histories. Furthermore, we provide a visual representation of the several layers inside a network to illustrate the attributes of a facial feature that may be acquired using Convolutional Neural Network (CNN) models.

Face Recognition, Image Processing, Computer Vision, Emotion Detection, OpenCV


IJTSRD64783
Volume-8 | Issue-3, June 2024
277-283
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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