Editor/Reviewer loginFrequency : 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
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"}
The paper explains the experiment and evaluation of CNN architecture.
The paper explains the effect of the optimizer.
The experiment is performed using CIFAR-10 datasets.
In the simulation, a performance evaluation of the algorithm is carried out.