AUTOMATIC FRUIT DETECTION USING MULTILAYER NEURAL NETWORK

AUTOMATIC FRUIT DETECTION USING MULTILAYER NEURAL NETWORK

Manasa C M 1, Dr. Hemanth S R 2

1 M-Tech Student, CSE, Maharaja Institute of Technology, Belavadi, Mandya, India, 571477

2Associate Professor, Department of CSE, Maharaja Institute of Technology, Belavadi, Mandya, India, 571477

ABSTRACT:

Agriculture has become an important thing in everyday life .Among this, fruits are a great thing in everyday life. Classification of fruits based on their accuracy is a decent approach to all the fruit sellers. There is much parallelism between apple and cherry and various kinds of similarities are present in many types of fruits, so the classification plays an important role. However, there are troubles in fruit classification using machine learning algorithms like Support Vector Machine (SVM) and Convolution Neural Network (CNN). So, the methods of CNN, pooling layers and fully connected network have been applied to overcome the problems. The CNN and pooling layers have been applied to extract the features of the fruits.

Keywords: Agriculture, Convolution Neural Network, machine learning, Support Vector Machine.