at Google ScholarTitle 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.
Vol. 14
(2020)
.
- pp. 927-945.
ISSN 1862-5355
DOI: https://doi.org/10.1007/s11634-020-00429-0
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: | 25 Oct 2023 11:50 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/56771 |