Purwono, Alfian Ma’arif, Wahyu Rahmaniar, Haris Imam Karim Fathurrahman, Aufaclav Zatu Kusuma Frisky, Qazi Mazhar Ul Haq
The application of deep learning technology has increased rapidly in recent years. Technologies in deep learning increasingly emulate natural human abilities, such as knowledge learning, problem-solving, and decision-making. In general, deep learning can carry out self-training without repetitive programming by humans. Convolutional neural networks (CNNs) are deep learning algorithms commonly used in wide applications. CNN is often used for image classification, segmentation, object detection, video processing, natural language processing, and speech recognition. CNN has four layers: convolution layer, pooling layer, fully connected layer, and non-linear layer. The convolutional layer uses kernel filters to calculate the convolution of the input image by extracting the fundamental features. The pooling layer combines two successive convolutional layers. The third layer is the fully connected layer, commonly called the convolutional output layer. The activation function defines the output of a neural network, such as 'yes' or 'no'. The most common and popular CNN activation functions are Sigmoid, Tanh, ReLU, Leaky ReLU, Noisy ReLU, and Parametric Linear Units. The organization and function of the visual cortex greatly influence CNN architecture because it is designed to resemble the neuronal connections in the human brain. Some of the popular CNN architectures are LeNet, AlexNet and VGGNet. © 2022, Association for Scientific Computing Electronics and Engineering (ASCEE). All rights reserved.
Universitas Harapan Bangsa, Jl. Raden Patah No. 100 Kedunglongsir Ledug Kembaran, Banyumas, 53182, Indonesia; Department of Electrical Engineering, Universitas Ahmad Dahlan, Banguntapan, Bantul, Yogyakarta, 55191, Indonesia; Department of Electronic Engineering, National Taipei University of Technology, Taipei, 10608, Taiwan; Institute of Visual Computing & Human-Centered Technology, Technische Universität Wien, Vienna, 1040, Austria; Department of Computer Science and Electronics, Universitas Gadjah Mada, Yogyakarta, Indonesia; Department of Computer Software Engineering, National University of Sciences and Technology, Islamabad, Pakistan
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