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Frequency : 12 issues per year

Subject : Computer Applications and Technology

ISSN : 2319–8656 (Online)

IJCATR Volume 13 Issue 8

The Performance of Convolutional Neural Network Architecture in Classification

Panca Mudjirahardjo, Aqil Gama Rahmansyah, Alya Shafa Dianti

10.7753/IJCATR1308.1011

keywords : convolutional neural network; optimizer; CIFAR10 datasets; CNN architecture; object classification

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ABSTRACT
BIBTEXT

In this paper, we study the performance of convolutional neural network (CNN) architecture for object classification. We evaluate three optimizers, i.e. ADAM, SGD and RMSprop and 5 convolutional layers use CIFAR10 datasets. We conduct the experiment with python program language. We evaluate the training, validation accuracy and training execution time.

@artical{p1382024ijcatr13081011,
Title = "The Performance of Convolutional Neural Network Architecture in Classification ",
Journal ="International Journal of Computer Applications Technology and Research (IJCATR)",
Volume = "13",
Issue ="8",
Pages ="115 - 122",
Year = "2024",
Authors ="Panca Mudjirahardjo, Aqil Gama Rahmansyah, Alya Shafa Dianti"}