GDL

Journal from gdlhub / 2018-07-25 16:01:01
Oleh : R. Putri Ayu Pramesti, Yeni Herdiyeni, Anto Satriyo Nugroho, Telkomnika
Dibuat : 2018-07-25, dengan 1 file

Keyword : ensemble classifier; naïve Bayes combination; weighted majority vote; weighted classifier
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/7615
Sumber pengambilan dokumen : WEB

Plant leaf identification using image can be constructed by ensemble classifier. Ensemble classifier executes classification of various features independently. This experiment utilized texture feature and geometry feature of plant leaf. Each classifier trained by specific feature produced different accuracy rate. To integrate the classification scores obtained by different classifiers, the results of the classification were weighted, so as the score obtained from better features contributed greater to the final results. Weighted classification results were combined to get the final result. The proposed method was evaluated using dataset comprises of 156 variety of plants with 4559 images. Weighting and combining classifier used in this study were Weighted Majority Vote (WMV) and Naïve Bayes Combination. The average accuracy of WMV method was 77.84%, while Naïve Bayes Combination was 94.62%.

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