Alexandr A. Kuzmenko, S. Kondratenko, K. Dergachev, Valery Spasennikov
{"title":"基于深度学习的Logo设计人机工程学支持","authors":"Alexandr A. Kuzmenko, S. Kondratenko, K. Dergachev, Valery Spasennikov","doi":"10.51130/graphicon-2020-2-4-42","DOIUrl":null,"url":null,"abstract":"Every year rendering logos becomes an increasingly important task in various fields. One of the most interesting methods for rendering logos is the use of neural networks. This paper proposes a method for rendering logos using a convolutional neural network (CNN), specially trained to classify objects based on a single keyword and to select parametric characteristics of the logo. Special attention is paid to the ergonomic evaluation of resulting logos and the feasibility of the proposed method is experimentally confirmed. The research has shown that the results obtained are superior compared to the most modern approaches.","PeriodicalId":344054,"journal":{"name":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Ergonomic Support for Logo Development Based on Deep Learning\",\"authors\":\"Alexandr A. Kuzmenko, S. Kondratenko, K. Dergachev, Valery Spasennikov\",\"doi\":\"10.51130/graphicon-2020-2-4-42\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Every year rendering logos becomes an increasingly important task in various fields. One of the most interesting methods for rendering logos is the use of neural networks. This paper proposes a method for rendering logos using a convolutional neural network (CNN), specially trained to classify objects based on a single keyword and to select parametric characteristics of the logo. Special attention is paid to the ergonomic evaluation of resulting logos and the feasibility of the proposed method is experimentally confirmed. The research has shown that the results obtained are superior compared to the most modern approaches.\",\"PeriodicalId\":344054,\"journal\":{\"name\":\"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.51130/graphicon-2020-2-4-42\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 30th International Conference on Computer Graphics and Machine Vision (GraphiCon 2020). Part 2","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51130/graphicon-2020-2-4-42","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ergonomic Support for Logo Development Based on Deep Learning
Every year rendering logos becomes an increasingly important task in various fields. One of the most interesting methods for rendering logos is the use of neural networks. This paper proposes a method for rendering logos using a convolutional neural network (CNN), specially trained to classify objects based on a single keyword and to select parametric characteristics of the logo. Special attention is paid to the ergonomic evaluation of resulting logos and the feasibility of the proposed method is experimentally confirmed. The research has shown that the results obtained are superior compared to the most modern approaches.