The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Nosso grupo de pesquisa tem trabalhado na previsão de atratividade, raciocínio e até aprimoramento de conteúdo multimídia, o que chamamos de “computação de atratividade”. A atratividade inclui capacidade de impressão, capacidade de instagram, capacidade de memorização, capacidade de clique e assim por diante. A análise dessa atratividade geralmente era feita por profissionais experientes, mas revelamos experimentalmente que a inteligência artificial (IA) baseada em big data multimídia pode imitar ou reproduzir as habilidades dos profissionais em alguns casos. Neste artigo, apresentamos alguns dos trabalhos representativos e possíveis aplicações na vida real de nossa computação de atratividade para mídia de imagem.
Toshihiko YAMASAKI
The University of Tokyo
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Toshihiko YAMASAKI, "Attractiveness Computing in Image Media" in IEICE TRANSACTIONS on Fundamentals,
vol. E106-A, no. 9, pp. 1196-1201, September 2023, doi: 10.1587/transfun.2022IMI0001.
Abstract: Our research group has been working on attractiveness prediction, reasoning, and even enhancement for multimedia content, which we call “attractiveness computing.” Attractiveness includes impressiveness, instagrammability, memorability, clickability, and so on. Analyzing such attractiveness was usually done by experienced professionals but we have experimentally revealed that artificial intelligence (AI) based on big multimedia data can imitate or reproduce professionals' skills in some cases. In this paper, we introduce some of the representative works and possible real-life applications of our attractiveness computing for image media.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2022IMI0001/_p
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@ARTICLE{e106-a_9_1196,
author={Toshihiko YAMASAKI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Attractiveness Computing in Image Media},
year={2023},
volume={E106-A},
number={9},
pages={1196-1201},
abstract={Our research group has been working on attractiveness prediction, reasoning, and even enhancement for multimedia content, which we call “attractiveness computing.” Attractiveness includes impressiveness, instagrammability, memorability, clickability, and so on. Analyzing such attractiveness was usually done by experienced professionals but we have experimentally revealed that artificial intelligence (AI) based on big multimedia data can imitate or reproduce professionals' skills in some cases. In this paper, we introduce some of the representative works and possible real-life applications of our attractiveness computing for image media.},
keywords={},
doi={10.1587/transfun.2022IMI0001},
ISSN={1745-1337},
month={September},}
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TY - JOUR
TI - Attractiveness Computing in Image Media
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1196
EP - 1201
AU - Toshihiko YAMASAKI
PY - 2023
DO - 10.1587/transfun.2022IMI0001
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E106-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2023
AB - Our research group has been working on attractiveness prediction, reasoning, and even enhancement for multimedia content, which we call “attractiveness computing.” Attractiveness includes impressiveness, instagrammability, memorability, clickability, and so on. Analyzing such attractiveness was usually done by experienced professionals but we have experimentally revealed that artificial intelligence (AI) based on big multimedia data can imitate or reproduce professionals' skills in some cases. In this paper, we introduce some of the representative works and possible real-life applications of our attractiveness computing for image media.
ER -