Crop disease image recognition based on transfer learning

Sisi Fang, Yuan Yuan, Lei Chen, Jian Zhang, Miao Li, Shide Song

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

7 Scopus citations

Abstract

Machine learning has been widely applied to the crop disease image recognition. Traditional machine learning needs to satisfy two basic assumptions: (1) The training and test data should be under the same distribution; (2) A large scale of labeled training samples is required to learn a reliable classification model. However, in many cases, these two assumptions cannot be satisfied. In the field of agriculture, there are not enough labeled crop disease images. In order to solve this problem, the paper proposed a method which introduced transfer learning to the crop disease image recognition. Firstly, the double Otsu method was applied to obtain the spot images of five kinds of cucumber and rice diseases. Then, color feature, texture feature and shape feature of spot images were extracted. Next, the TrAdaBoost-based method and other baseline methods were used to identify diseases. And experimental results indicate that the TrAdaBoost-based method can implement samples transfer between the auxiliary and target domain and achieve the better results than the other baseline methods. Meanwhile, the results show that transfer learning is helpful in the crop disease image recognition while the training sample is not enough.

Original languageEnglish
Title of host publicationImage and Graphics - 9th International Conference, ICIG 2017, Revised Selected Papers
EditorsYao Zhao, David Taubman, Xiangwei Kong
PublisherSpringer Verlag
Pages545-554
Number of pages10
ISBN (Print)9783319716060
DOIs
StatePublished - 2017
Externally publishedYes
Event9th International Conference on Image and Graphics, ICIG 2017 - Shanghai, China
Duration: 13 Sep 201715 Sep 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10666 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Image and Graphics, ICIG 2017
Country/TerritoryChina
CityShanghai
Period13/09/1715/09/17

Keywords

  • Crop diseases
  • Image recognition
  • Target domain
  • The spot images
  • Transfer learning

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