書誌事項
- タイトル別名
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- キカイ ガクシュウ ニ ヨル RAW ゲンゾウ ギジュツ ノ カイハツ
- Development of RAW Image Format Converter Using Deep Learning
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type:Article
RAW development is an operation manually performed by a person in order to finish a photograph according to his / her desire. At this time, many image adjustment parameters are set, and confirmation and adjustment are repeated. The work requires much time and effort, and it is very difficult to make many photos taken into the desired images. However, if deep learning is used, learning RAW images and photographs after RAW development may create photographs of the same level as manual RAW development. In this research, we succeeded in developing a machine learning model that performs RAW development using RAW data as input. We also aimed to improve the processing speed of learning using GPGPU. As a result of comparing processing in which RAW development is performed for 100 images with a single multi-core CPU using a parallel program and processing using a GPGPU, it is shown that the latter can be significantly faster.
identifier:http://repository.seikei.ac.jp/dspace/handle/10928/1175
収録刊行物
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- 成蹊大学理工学研究報告 = The journal of the Faculty of Science and Technology, Seikei University
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成蹊大学理工学研究報告 = The journal of the Faculty of Science and Technology, Seikei University 56 (1), 9-14, 2019-06-01
成蹊大学理工学部
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詳細情報 詳細情報について
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- CRID
- 1390291767730208128
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- NII論文ID
- 120006724986
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- NII書誌ID
- AA1203510X
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- ISSN
- 18802265
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- NDL書誌ID
- 029966158
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- IRDB
- NDL
- CiNii Articles