Literature DB >> 16252344

Identification of rice seed varieties using neural network.

Zhao-yan Liu1, Fang Cheng, Yi-bin Ying, Xiu-qin Rao.   

Abstract

A digital image analysis algorithm based color and morphological features was developed to identify the six varieties (ey7954, syz3, xs11, xy5968, xy9308, z903) rice seeds which are widely planted in Zhejiang Province. Seven color and fourteen morphological features were used for discriminant analysis. Two hundred and forty kernels used as the training data set and sixty kernels as the test data set in the neural network used to identify rice seed varieties. When the model was tested on the test data set, the identification accuracies were 90.00%, 88.00%, 95.00%, 82.00%, 74.00%, 80.00% for ey7954, syz3, xs11, xy5968, xy9308, z903 respectively.

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Year:  2005        PMID: 16252344      PMCID: PMC1390657          DOI: 10.1631/jzus.2005.B1095

Source DB:  PubMed          Journal:  J Zhejiang Univ Sci B        ISSN: 1673-1581            Impact factor:   3.066


  4 in total

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Journal:  Sensors (Basel)       Date:  2015-07-01       Impact factor: 3.576

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4.  iRSVPred: A Web Server for Artificial Intelligence Based Prediction of Major Basmati Paddy Seed Varieties.

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Journal:  Front Plant Sci       Date:  2020-02-25       Impact factor: 5.753

  4 in total

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