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GPU Based Image Classification using Convolutional Neural Network Chicken Dishes Classification

机译:使用卷积神经网络鸡肉菜肴分类的基于GPU的图像分类

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The internet makes human life easier, one of them is in orderingfood. By only using smartphones and opening food delivery features,in the application, consumers can order food from restaurants thatcollaborate with the e-commerce. The case study that we did wasclassifying the types of chicken dishes namely “ayam geprek”,“ayam goreng”, and “ayam bakar” using CNN method. CNNmethod is a popular method for image classification. This research isdoing image classification using CNN method based on GPU. Fromseveral models built, obtained the best model with an accuracy of99% and training speed about 233 seconds. While for comparison ofCNN method based on CPU and GPU obtained the conclusion thatthe most rapid training process using GPU.
机译:互联网使人们的生活更加轻松,其中之一就是订购食物。通过仅使用智能手机并打开送餐功能,在应用程序中,消费者可以从与电子商务合作的餐馆订购食物。我们所做的案例研究使用CNN方法对鸡肉菜肴的类型进行了分类,即“ ayam geprek”,“ ayam goreng”和“ ayam bakar”。 CNNmethod是一种流行的图像分类方法。这项研究正在使用基于GPU的CNN方法进行图像分类。从建立的几个模型中,以99%的准确度和约233秒的训练速度获得了最佳模型。为了比较基于CPU和GPU的CNN方法,得出了使用GPU训练最快的结论。

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