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} }