PERFORMANCE COMPARISON OF GRADIENT-BASED CONVOLUTIONAL NEURAL NETWORK OPTIMIZERS FOR FACIAL EXPRESSION RECOGNITION

PERFORMANCE COMPARISON OF GRADIENT-BASED CONVOLUTIONAL NEURAL NETWORK OPTIMIZERS FOR FACIAL EXPRESSION RECOGNITION

A convolutional neural network (CNN) is one of the machine learning models that achieve excellent success in recognizing human facial expressions. Technological developments have given birth to many optimizers that can be used to train the CNN model. Therefore, this study focuses on implementing and...

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Bibliographic Details
Main Authors: Sri Nurdiati, Mohamad Khoirun Najib, Fahren Bukhari, Refi Revina, Fitra Nuvus Salsabila
Format: Article
Language:English
Published: Universitas Pattimura 2022-09-01
Series:Barekeng
Subjects:
alexnet architecture
, confusion matrix
convolutional neural network
deep learning
facial expression recognition
gradient-based optimizer
Online Access:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/6105
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