계산 이미지의 탄생 - 장치에서 알고리즘으로 -
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 박평종 | - |
dc.date.accessioned | 2023-03-08T12:54:53Z | - |
dc.date.available | 2023-03-08T12:54:53Z | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 1228-503X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/63073 | - |
dc.description.abstract | Abstract This article deals with the changes triggered by artificial intelligence related to image production. The image originally started as a “manual image” drawn by human hands and then differentiated into a “technical image” produced by apparatus in the 19th century. Since then, with the development of image generation algorithms, the automaticity of image production has become more advanced. This generative model, represented by GAN, produces images only by 'calculation' based on probability and statistics. Currently, GAN is receiving the most attention in the field of computer vision, and it excels in various tasks such as creating high-resolution images, translating images, and compositing photos. GAN learns the original photos and creates an image similar to it, which goes beyond the limitations of apparatus such as human hands and cameras. This 'computational image' belongs to the category of 'technical image' in a broad sense, but differs from photography, the first technical image in that there is no indication object. In addition, the automaticity of the program, the nature of the apparatus, is accelerating the exclusion of humans from the image production process in an extreme form. As a result, humans cannot reflect their intentions in image production and are in a position to become a simple consumer of images. | - |
dc.format.extent | 15 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 한국사진학회 | - |
dc.title | 계산 이미지의 탄생 - 장치에서 알고리즘으로 - | - |
dc.title.alternative | The birth of computational image - from apparatus to algorithm - | - |
dc.type | Article | - |
dc.identifier.bibliographicCitation | AURA, no.46, pp 18 - 32 | - |
dc.identifier.kciid | ART002695412 | - |
dc.description.isOpenAccess | N | - |
dc.citation.endPage | 32 | - |
dc.citation.number | 46 | - |
dc.citation.startPage | 18 | - |
dc.citation.title | AURA | - |
dc.publisher.location | 대한민국 | - |
dc.subject.keywordAuthor | Artificial intelligence | - |
dc.subject.keywordAuthor | Algorithm | - |
dc.subject.keywordAuthor | GAN | - |
dc.subject.keywordAuthor | Technical image | - |
dc.subject.keywordAuthor | Vilem Flusser | - |
dc.description.journalRegisteredClass | kci | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
84, Heukseok-ro, Dongjak-gu, Seoul, Republic of Korea (06974)02-820-6194
COPYRIGHT 2019 Chung-Ang University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.