%0 Conference Paper %1 conf/apsipa/ShiWWLY19 %A Shi, Xinjie %A Wang, Tianqi %A Wang, Lan %A Liu, Hanjun %A Yan, Nan %B APSIPA %D 2019 %I IEEE %K dblp %P 939-944 %T Hybrid Convolutional Recurrent Neural Networks Outperform CNN and RNN in Task-state EEG Detection for Parkinson's Disease. %U http://dblp.uni-trier.de/db/conf/apsipa/apsipa2019.html#ShiWWLY19 %@ 978-1-7281-3248-8

@inproceedings{conf/apsipa/ShiWWLY19, added-at = {2020-03-13T00:00:00.000+0100}, author = {Shi, Xinjie and Wang, Tianqi and Wang, Lan and Liu, Hanjun and Yan, Nan}, biburl = {https://www.bibsonomy.org/bibtex/2e010b655f7b8c923a5d5c1b4b3faf23f/dblp}, booktitle = {APSIPA}, crossref = {conf/apsipa/2019}, ee = {https://doi.org/10.1109/APSIPAASC47483.2019.9023190}, interhash = {4db68db9bed887b1013ef61781a3cefe}, intrahash = {e010b655f7b8c923a5d5c1b4b3faf23f}, isbn = {978-1-7281-3248-8}, keywords = {dblp}, pages = {939-944}, publisher = {IEEE}, timestamp = {2020-03-14T12:16:56.000+0100}, title = {Hybrid Convolutional Recurrent Neural Networks Outperform CNN and RNN in Task-state EEG Detection for Parkinson's Disease.}, url = {http://dblp.uni-trier.de/db/conf/apsipa/apsipa2019.html#ShiWWLY19}, year = 2019 }