Penerapan Convolutional Neural Network Deep Learningdalam Pendeteksian Citra Biji Jagung Kering

Penerapan Convolutional Neural Network Deep Learningdalam Pendeteksian Citra Biji Jagung Kering

convolutionneuralnetwork, deeplearning, dry corn, image, detection

Corn kernels detection can be implemented in industry area. This can be implemented in the selection and packaging the corn kernels before it is distributed. This technique can be implemented in the selection and packaging machine to detect corn kernels accurately.Corn kernel images was used before it is implemented in real-time. The objective of this research was corn kernel detection using Convolutional Neural Network (CNN) deep learning. This technique consists of 3 main stages, the first preprocessing or normalizing the input of corn kernels image data by wrapping and cropping, both modeling and training the system, and testing. The experiment used CNN method to classifyimages of dry corn kernels andto determine the accuracy value. This research used 20 dry corn kernels images as testing from 80dry corn kernels images which used in training dataset. The accuracy of detection was dependent from the size of image and position when the image was taken. The accuracy is around 80% -100% by using 7 convolutional layers and the average of accuracy for testing data was0,90296.The convolutional layer which implemented in CNN has the strength to detect features in the input image.

Arum TiaraSari1, Emy Haryatmi

https://jurnal.iaii.or.id/index.php/RESTI/issue/view/22

Universitas Gunadarma

30 april 2021

Fajar bagus W

PDF

Indonesia

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