Implementation of Deep Learning Using Convolutional Neural Network for Wood Image Classification


Authors : Ditha Putri Pramesti; Sriyani Violina

Volume/Issue : Volume 6 - 2021, Issue 1 - January

Google Scholar : http://bitly.ws/9nMw

Scribd : https://bit.ly/39H145B

The use of wood cannot be separated from human life. The benefits of wood that are often used are as material for household appliances, furniture, and buildings. Wood consists of a cell wall of chemical compounds so that it has fibers. There are various types of wood so that they can be classified based on the group. There are 8550 wood images that will be classified using the VGG16 and VGG19 architectures. VGG network is a Convolutional Neural Network architecture using input in the form of an RGB image measuring 224x224 pixels. We use both architectures because by using them we get the highest results with an accuracy value of 0.79% and 0.78%.

Keywords : Convolutional Neural Network, Deep Learning, VGG16, VGG19.

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