Three Mixture of Odor Classification using Convolutional Neural Network

Abstract

Convolutional Neural Network (CNN) is widely used in image classification problems because of its good performance, however, vector-based classification using a convolutional neural network is rarely utilized. Researchers tend to use another method of artificial neural networks, such as backpropagation neural network, probability neural networks, as the classifier for vector-based classification problems. In this paper, we would like to use a CNN classifier in the problems of 6 classes of three mixture of odor using 4 and 6 channels of sensors. In order to compare the performance of the vector based convolutional neural network, back-propagation neural network is also used to classify the same vector-based odor classification problems. The Experiment results show that vector-based convolutional neural network yields a quite high recognition rate compare with that of backpropagation neural network. The vector-based convolutional neural network produced more than 95% recognition rate for each data type, while the backpropagation neural network can only achieve a maximum recognition rate of 56% for each data type.