Ikuro Sato, Guoqing Liu, Kohta Ishikawa, Teppei Suzuki, Masayuki Tanaka. Does End-to-End Trained Deep Model Always Perform Better than Non-End-to-End Counterpart?. In Sos S. Agaian, Karen O. Egiazarian, Atanas P. Gotchev, editors, Image Processing: Algorithms and Systems XIX, Virtual Event, 11-28 January 2021. Ingenta, 2021. [doi]
@inproceedings{SatoLIST21,
title = {Does End-to-End Trained Deep Model Always Perform Better than Non-End-to-End Counterpart?},
author = {Ikuro Sato and Guoqing Liu and Kohta Ishikawa and Teppei Suzuki and Masayuki Tanaka},
year = {2021},
doi = {10.2352/ISSN.2470-1173.2021.10.IPAS-240},
url = {https://doi.org/10.2352/ISSN.2470-1173.2021.10.IPAS-240},
researchr = {https://researchr.org/publication/SatoLIST21},
cites = {0},
citedby = {0},
booktitle = {Image Processing: Algorithms and Systems XIX, Virtual Event, 11-28 January 2021},
editor = {Sos S. Agaian and Karen O. Egiazarian and Atanas P. Gotchev},
publisher = {Ingenta},
}