Three mixture of odor classification using convolutional neural network

Ida Bagus Krishna Yoga Utama, Akhmad Faqih, Benyamin Kusumoputro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publication2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728118987
DOIs
Publication statusPublished - Jul 2019
Event16th International Conference on Quality in Research, QIR 2019 - Padang, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

Name2019 16th International Conference on Quality in Research, QIR 2019 - International Symposium on Electrical and Computer Engineering

Conference

Conference16th International Conference on Quality in Research, QIR 2019
CountryIndonesia
CityPadang
Period22/07/1924/07/19

Keywords

  • Neural network
  • Odor classification
  • Vector-based convolutional neural network

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