%0 Journal Article %1 journals/nn/WuZGQZZL22 %A Wu, Zhenzhi %A Zhang, Zhihong %A Gao, Huanhuan %A Qin, Jun %A Zhao, Rongzhen %A Zhao, Guangshe %A Li, Guoqi %D 2022 %J Neural Networks %K dblp %P 184-194 %T Modeling learnable electrical synapse for high precision spatio-temporal recognition. %U http://dblp.uni-trier.de/db/journals/nn/nn149.html#WuZGQZZL22 %V 149

@article{journals/nn/WuZGQZZL22, added-at = {2022-04-27T00:00:00.000+0200}, author = {Wu, Zhenzhi and Zhang, Zhihong and Gao, Huanhuan and Qin, Jun and Zhao, Rongzhen and Zhao, Guangshe and Li, Guoqi}, biburl = {https://www.bibsonomy.org/bibtex/2ce09ee3c8502190f23dfdc4e44cfb2b9/dblp}, ee = {https://doi.org/10.1016/j.neunet.2022.02.006}, interhash = {de9dc2e93ad960a4bea0d07745191f5a}, intrahash = {ce09ee3c8502190f23dfdc4e44cfb2b9}, journal = {Neural Networks}, keywords = {dblp}, pages = {184-194}, timestamp = {2024-04-09T05:23:49.000+0200}, title = {Modeling learnable electrical synapse for high precision spatio-temporal recognition.}, url = {http://dblp.uni-trier.de/db/journals/nn/nn149.html#WuZGQZZL22}, volume = 149, year = 2022 }