Abstract:
Most of the today’s new and innovative artificial
intelligence applications are based on the
artificial neural types of networks to capture,
interpret and analyze various kind of data. A
Convolutional Neural Network is a type of
artificial neural network used primarily for image
recognition and processing due to its ability to
patterns in images. A deep learning algorithm is
adopted to classify images and detect objects in an
image with the neural network. In this study,
Convolutional Neural Networks Model is used for
performing automatic feature extraction on
binary classification with leaf image dataset. It
works by investigating and processing large
amount of data in a grid format and then
extracting important features for classification
detection. It is discussed in this study the use of
deep learning techniques to automatically detect
diseases in plants. Further, it emphasizes the
working principles of Convolutional Neural
Networks. Hence, the study intends to present a
comprehensive way of the modeling techniques.
Moreover, the study seeks fundamentals on deep
learning mechanisms which is useful to beginners
on the area of artificial intelligence. Therefore,
this study is carried out intentionally as a case
study which emphasizes the automatic leaf image
binary classification. The findings of the present
study showed 81.3% of the maximum accuracy of
the modeling.
