Classification of Two Comic Books based on Convolutional Neural Networks
Unphotographic images are the powerful representations described various situations. Thus, understanding intellectual products such as comics and picture books is one of the important topics in the field of artificial intelligence. Hence, stepwise analysis of a comic story, i.e., features of a part...
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| Vydáno v: | ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal Ročník 6; číslo 1; s. 5 - 12 |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina japonština |
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Salamanca
Ediciones Universidad de Salamanca
12.01.2017
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| ISSN: | 2255-2863, 2255-2863 |
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| Abstract | Unphotographic images are the powerful representations described various situations. Thus, understanding intellectual products such as comics and picture books is one of the important topics in the field of artificial intelligence. Hence, stepwise analysis of a comic story, i.e., features of a part of the image, information features, features relating to continuous scene etc., was pursued. Especially, the length and each scene of four-scene comics are limited so as to ensure a clear interpretation of the contents.In this study, as the first step in this direction, the problem to classify two four-scene comics by the same artists were focused as the example. Several classifiers were constructed by utilizing a Convolutional Neural Network(CNN), and the results of classification by a human annotator and by a computational method were compared.From these experiments, we have clearly shown that CNN is efficient way to classify unphotographic gray scaled images and found that characteristic features of images to classify incorrectly. |
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| AbstractList | Unphotographic images are the powerful representations described various situations. Thus, understanding intellectual products such as comics and picture books is one of the important topics in the field of artificial intelligence. Hence, stepwise analysis of a comic story, i.e., features of a part of the image, information features, features relating to continuous scene etc., was pursued. Especially, the length and each scene of four-scene comics are limited so as to ensure a clear interpretation of the contents.In this study, as the first step in this direction, the problem to classify two four-scene comics by the same artists were focused as the example. Several classifiers were constructed by utilizing a Convolutional Neural Network(CNN), and the results of classification by a human annotator and by a computational method were compared.From these experiments, we have clearly shown that CNN is efficient way to classify unphotographic gray scaled images and found that characteristic features of images to classify incorrectly. Unphotographic images are the powerful representations described various situations. Thus, understanding intellectual products such as comics and picture books is one of the important topics in the field of artificial intelligence. Hence, stepwise analysis of a comic story, i.e., features of a part of the image, information features, features relating to continuous scene etc., was pursued. Especially, the length and each scene of four-scene comics are limited so as to ensure a clear interpretation of the contents. In this study, as the first step in this direction, the problem to classify two four-scene comics by the same artists were focused as the example. Several classifiers were constructed by utilizing a Convolutional Neural Network(CNN), and the results of classification by a human annotator and by a computational method were compared. From these experiments, we have clearly shown that CNN is efficient way to classify unphotographic gray scaled images and found that characteristic features of images to classify incorrectly. |
| Author | Isahara, Hitoshi Suenaga, Toshinori Ueno, Miki |
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| Cites_doi | 10.1016/0031-3203(82)90024-3 |
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| DOI | 10.14201/adcaij201761512 |
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| References | Krizhevsky (ref4) 2012 Tokui (ref6) 2015 Le Quoc (ref5) 2013 ref3 Eitz (ref1) 2012; 31 Fujino (ref2) 2007 |
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| SubjectTerms | Artificial neural networks Artists comic engineering Comics Computación computational model of comics Computing convolutional neural network Electronic computers. Computer science Image classification Information Technology Informótica Neural networks QA75.5-76.95 |
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| Title | Classification of Two Comic Books based on Convolutional Neural Networks |
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