With the increase in research on AI(Artificial Intelligence),the importance of DL(Deep Learning)in various fields,such as materials,biotechnology,genomes,and new drugs,is increasing significantly,thereby increasing th...With the increase in research on AI(Artificial Intelligence),the importance of DL(Deep Learning)in various fields,such as materials,biotechnology,genomes,and new drugs,is increasing significantly,thereby increasing the number of deep-learning framework users.However,to design a deep neural network,a considerable understanding of the framework is required.To solve this problem,a GUI(Graphical User Interface)-based DNN(Deep Neural Network)design tool is being actively researched and developed.The GUI-based DNN design tool can design DNNs quickly and easily.However,the existing GUI-based DNN design tool has certain limitations such as poor usability,framework dependency,and difficulty encountered in changing GUI components.In this study,a deep learning algorithm that solves the problem of poor usability was developed using a template to increase the accessibility for users.Moreover,the proposed tool was developed to save and share only the necessary parts for quick operation.To solve the framework dependency,we applied ONNX(Open Neural Network Exchange),which is an exchange standard for neural networks,and configured it such that DNNs designed with the existing deep-learning framework can be imported.Finally,to address the difficulty encountered in changing GUI components,we defined and developed the JSON format to quickly respond to version updates.The developed DL neural network designer was validated by running it with KISTI’s supercomputer-based AI Studio.展开更多
图形用户界面(Graphical User Interface,GUI)作为特殊的一类外观设计,低保真原型和高保真原型是否能以相似设计合案申请引发较多争议。文章通过分析相似设计的立法本意,结合设计行业对低保真原型、高保真原型的认知,对于图文排布、交...图形用户界面(Graphical User Interface,GUI)作为特殊的一类外观设计,低保真原型和高保真原型是否能以相似设计合案申请引发较多争议。文章通过分析相似设计的立法本意,结合设计行业对低保真原型、高保真原型的认知,对于图文排布、交互逻辑较为相似的低保真和高保真原型能否合案申请提出从以下三个方面思考是否相似,即图标、图案在界面中的占比,图标及背景的变化情况以及参考图与设计构思的关联性。具体案例还需结合实际情况具体分析。展开更多
基金This research was supported by the KISTI Program(No.K-20-L02-C05-S01)the EDISON Program through the National Research Foundation of Korea(NRF)(No.NRF-2011-0020576).A grant was also awarded by the Ministry of Science and ICT(MSIT)under the Program for Returners for R&D.
文摘With the increase in research on AI(Artificial Intelligence),the importance of DL(Deep Learning)in various fields,such as materials,biotechnology,genomes,and new drugs,is increasing significantly,thereby increasing the number of deep-learning framework users.However,to design a deep neural network,a considerable understanding of the framework is required.To solve this problem,a GUI(Graphical User Interface)-based DNN(Deep Neural Network)design tool is being actively researched and developed.The GUI-based DNN design tool can design DNNs quickly and easily.However,the existing GUI-based DNN design tool has certain limitations such as poor usability,framework dependency,and difficulty encountered in changing GUI components.In this study,a deep learning algorithm that solves the problem of poor usability was developed using a template to increase the accessibility for users.Moreover,the proposed tool was developed to save and share only the necessary parts for quick operation.To solve the framework dependency,we applied ONNX(Open Neural Network Exchange),which is an exchange standard for neural networks,and configured it such that DNNs designed with the existing deep-learning framework can be imported.Finally,to address the difficulty encountered in changing GUI components,we defined and developed the JSON format to quickly respond to version updates.The developed DL neural network designer was validated by running it with KISTI’s supercomputer-based AI Studio.
文摘图形用户界面(Graphical User Interface,GUI)作为特殊的一类外观设计,低保真原型和高保真原型是否能以相似设计合案申请引发较多争议。文章通过分析相似设计的立法本意,结合设计行业对低保真原型、高保真原型的认知,对于图文排布、交互逻辑较为相似的低保真和高保真原型能否合案申请提出从以下三个方面思考是否相似,即图标、图案在界面中的占比,图标及背景的变化情况以及参考图与设计构思的关联性。具体案例还需结合实际情况具体分析。
