CNN with multi stage image data augmentation methods for indonesia rare and protected orchids classification

Dimas Sony Dewantara, Rachmat Hidayat, Heru Susanto, Aniati Murni Arymurthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Image classification of Indonesian rare and protected orchids is one of the solutions to prevent illegal trade, especially in online commerce that uses images as one of the display features. Image classification using deep Convolutional Neural Network (CNN) is a major breakthrough at this time where the extraction feature is done automatically through a series of convolution layers. Deep CNN requires a lot of training data to produce a good classification result. Image data of Indonesian rare and protected orchids are relativHeruely difficult to obtain when searched through relevant sources to avoid inaccurate information. In this paper, we propose a new approach of multi-stage image data augmentation to overcome limited data problem in deep CNN for Indonesian rare and protected orchids image classification. Image data augmentation method using basic image augmentation divided into geometric transformation and distortion injection. ResNet with transfer learning as CNN model is used for the classification. The proposed system is experimentally evaluated in the form of data augmentation methods combination such as stage 1 and stage 2 augmented dataset and results show its convincing performance compared to existing methods.

Original languageEnglish
Title of host publication2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728169071
DOIs
Publication statusPublished - 16 Sep 2020
Event2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020 - Virtual, Bogor, Indonesia
Duration: 16 Sep 202017 Sep 2020

Publication series

Name2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020

Conference

Conference2020 International Conference on Computer Science and Its Application in Agriculture, ICOSICA 2020
Country/TerritoryIndonesia
CityVirtual, Bogor
Period16/09/2017/09/20

Keywords

  • Convolutional Neural Network
  • Image Classification
  • Image Data Augmentation
  • Indonesia Rare and Protected Orchids
  • ResNet
  • Transfer Learning

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