GDL

Journal from gdlhub / 2017-11-06 11:08:57
Oleh : Joko Siswantoro, Anton Satria Prabuwono, Azizi Abdullah, Bahari Indrus, ITB
Dibuat : 2017-11-06, dengan 1 file

Keyword : Kalman filter; linear model; natural produce; neural network; recognition.
Url : http://journals.itb.ac.id/index.php/jictra/article/view/2612
Sumber pengambilan dokumen : WEB

Natural produce recognition is a classification problem with various applications in the food industry. This paper proposes a natural produce recognition method using computer vision. The proposed method uses simple features consisting of statistical color features and the derivative of radius function. A hybrid neural network and linear model based on a Kalman filter (NN-LMKF) was employed as classifier. One thousand images from ten categories of natural produce were used to validate the proposed method by using 5-fold cross validation. The experimental result showed that the proposed method achieved classification accuracy of 98.40%. This means it performed better than the original neural network and k-nearest neighborhood

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