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- SASAKI Kazuma
- Waseda University
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- OGATA Tetsuya
- Waseda University Artificial Ingelligence Research Center, AIST
Bibliographic Information
- Other Title
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- 手描きスケッチを扱う深層学習モデル
- テガキ スケッチ オ アツカウ シンソウ ガクシュウ モデル
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Abstract
<p>Hand-drawn sketch allows humans to represent visual information in the real world. One of difficulties for computational systems to take hand-drawn sketches is coming from their various type of transformations when we want to compare them with realistic photo images, or consider drawing process. In this article we discuss about deep learning based methods which can take these various types of transformations. First we show how do convolutional neural network based models recognize or generate sketches as static raster images. After that we also discuss other researches which utilize recurrent neural networks in order to process sketches as dynamical processes. In the latter part of the discussion, we briefly introduce out work about integration of visuomotor information in robot's drawing process.</p>
Journal
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- NIHON GAZO GAKKAISHI (Journal of the Imaging Society of Japan)
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NIHON GAZO GAKKAISHI (Journal of the Imaging Society of Japan) 56 (2), 177-186, 2017
The Imaging Society of Japan
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Details 詳細情報について
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- CRID
- 1390001204099171968
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- NII Article ID
- 130006767905
- 40021182637
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- NII Book ID
- AA1137305X
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- ISSN
- 18804675
- 13444425
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- NDL BIB ID
- 028157461
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed