A Deep Learning Model Generation Method for Code Reuse and Automatic Machine Learning

被引:3
作者
Lee, Keon Myung [1 ]
Hwang, Kyoung Soon [1 ]
Kim, Kwang Il [1 ]
Lee, Sang Hyun [1 ]
Park, Ki Sun [1 ]
机构
[1] Chungbuk Natl Univ, Dept Comp Sci, Cheongju, Chungbuk, South Korea
来源
PROCEEDINGS OF THE 2018 CONFERENCE ON RESEARCH IN ADAPTIVE AND CONVERGENT SYSTEMS (RACS 2018) | 2018年
基金
新加坡国家研究基金会;
关键词
Machine learning; automated machine learning; deep learning and convolutional neural networks;
D O I
10.1145/3264746.3264787
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In recent years, deep neural networks are active in numerous applications such as predictive, advertising and healthcare applications using of image, voice and text recognitions. However, deep neural networks are useful methods but usually require a proper modeling to construct a deep neural network method in any application. Designing a model is a tedious task to be realized in the network, which opens an issue to design an effective software tool for modeling deep neural networks. To get an excellent model for deep neural networks, the developers should have sufficient understanding and experience for deep neural network methods. The developers also require coding skills with the deep learning frameworks and knowledge for the computing resources. This paper presents a software tool based on a Graphical User Interface (GUI) to develop deep neural network models, which train the models with external computing resources and automate the hyper-parameter tuning.
引用
收藏
页码:47 / 52
页数:6
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