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Predicting Brand Confusion in Imagery Markets Based on Deep Learning of Visual Advertisement Content

Title data

Nakayama, Atsuho ; Baier, Daniel:
Predicting Brand Confusion in Imagery Markets Based on Deep Learning of Visual Advertisement Content.
In: Advances in Data Analysis and Classification. (2020) .
ISSN 1862-5355

Further data

Item Type: Article in a journal
Refereed: Yes
Additional notes: Published in the Special Issue on Learning in Data Science: Theory, Methods and Applications
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XIV - Marketing and Innovation
Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XIV - Marketing and Innovation > Chair Business Administration XIV - Marketing and Innovation - Univ.-Prof. Dr. Daniel Baier
Faculties
Faculties > Faculty of Law, Business and Economics
Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Result of work at the UBT: Yes
DDC Subjects: 300 Social sciences > 330 Economics
Date Deposited: 03 Sep 2020 08:29
Last Modified: 14 Sep 2020 08:56
URI: https://eref.uni-bayreuth.de/id/eprint/56771