Deteksi Ras Kucing Menggunakan Compound Model Scaling Convolutional Neural Network
DOI:
https://doi.org/10.33050/tmj.v6i2.1704Abstract
Cat is one of a popular animals in the world. Number of cat breeds in the world only about 1%, so most are dominated by cats mixed or domestic cat. Nevertheless, there are so many different types of cat breeds in the world, that it is sometimes difficult to identify them. Therefore, we need a system that can recognize the types of cat breeds. One technique of deep learning that may apprehend and hit upon gadgets in a photograph is Convolutional Neural Network (CNN). CNN functionality is alleged because the nice technique in phrases of item detection and item recognition. The author used 9 different types of cat breeds containing 2700 images. The EfficientNet-B0 architecture is used on the system. The most optimal model has earned the accuracy of 95%.
Keywords : Deep Learning, Convolutional Neural Network (CNN), Cat breeds, EfficientNet-B0.
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Copyright (c) 2021 Nadia Azahro Choirunisa, Tita Karlita, Rengga Asmara
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