An Effective Deep Transfer Learning and Information Fusion Framework for Medical Visual Question Answering.
Feifan Liu|Yalei Peng|Max P. Rosen
| Anthology ID: | DBLP:conf/clef/LiuPR18 |
|---|---|
| Volume: | Experimental IR Meets Multilinguality, Multimodality, and Interaction - 10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9-12, 2019, Proceedings |
| Year: | 2019 |
| Venue: | Conference and Labs of the Evaluation Forum (CLEF) |
| Publisher: | Springer |
| Pages: | 238-247 |
| URL: | https://doi.org/10.1007/978-3-030-28577-7_20 |
| DOI: | https://doi.org/10.1007/978-3-030-28577-7_20 |
| DBLP: | conf/clef/LiuPR18 |
| BibTeX: |
@inproceedings{liu-2019-effective,
author = {Feifan Liu and
Yalei Peng and
Max P. Rosen},
editor = {Fabio Crestani and
Martin Braschler and
Jacques Savoy and
Andreas Rauber and
Henning M\"{u}ller and
David E. Losada and
Gundula Heinatz B\"{u}rki and
Linda Cappellato and
Nicola Ferro},
title = {{An Effective Deep Transfer Learning and Information Fusion Framework for Medical Visual Question Answering}},
booktitle = {{Experimental IR Meets Multilinguality, Multimodality, and Interaction - 10th International Conference of the CLEF Association, CLEF 2019, Lugano, Switzerland, September 9-12, 2019, Proceedings}},
series = {Lecture Notes in Computer Science},
volume = {11696},
pages = {238--247},
publisher = {Springer},
year = {2019},
url = {https://doi.org/10.1007/978-3-030-28577-7_20},
doi = {https://doi.org/10.1007/978-3-030-28577-7_20}
}