Article,

CONTRAST OF RESNET AND DENSENET BASED ON THE RECOGNITION OF SIMPLE FRUIT DATA SET

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International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE), 6 (1): 1-8 (January 2019)
DOI: 10.5121/ijcsitce.2019.6101

Abstract

In this paper, a fruit image data set is used to compare the efficiency and accuracy of two widely used Convolutional Neural Network, namely the ResNet and the DenseNet, for the recognition of 50 different kinds of fruits. In the experiment, the structure of ResNet-34 and DenseNet_BC-121 (with bottleneck layer) are used. The mathematic principle, experiment detail and the experiment result will be explained through comparison.

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