TY - GEN
T1 - Famous Companies Use More Letters in Logo
T2 - International Workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021
AU - Nishi, Shintaro
AU - Kadota, Takeaki
AU - Uchida, Seiichi
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number JP17H06100.
Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - This paper analyzes a large number of logo images from the LLD-logo dataset, by recent deep learning-based techniques, to understand not only design trends of logo images and but also the correlation to their owner company. Especially, we focus on three correlations between logo images and their text areas, between the text areas and the number of followers on Twitter, and between the logo images and the number of followers. Various findings include the weak positive correlation between the text area ratio and the number of followers of the company. In addition, deep regression and deep ranking methods can catch correlations between the logo images and the number of followers.
AB - This paper analyzes a large number of logo images from the LLD-logo dataset, by recent deep learning-based techniques, to understand not only design trends of logo images and but also the correlation to their owner company. Especially, we focus on three correlations between logo images and their text areas, between the text areas and the number of followers on Twitter, and between the logo images and the number of followers. Various findings include the weak positive correlation between the text area ratio and the number of followers of the company. In addition, deep regression and deep ranking methods can catch correlations between the logo images and the number of followers.
UR - http://www.scopus.com/inward/record.url?scp=85115331864&partnerID=8YFLogxK
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U2 - 10.1007/978-3-030-86198-8_8
DO - 10.1007/978-3-030-86198-8_8
M3 - Conference contribution
AN - SCOPUS:85115331864
SN - 9783030861971
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 97
EP - 111
BT - Document Analysis and Recognition – ICDAR 2021 Workshops - Proceedings
A2 - Barney Smith, Elisa H.
A2 - Pal, Umapada
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 5 September 2021 through 10 September 2021
ER -