SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-World Verification

Songxuan Lai, Lianwen Jin, Luojun Lin, Yecheng Zhu, Huiyun Mao. SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-World Verification. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020. pages 735-742, AAAI Press, 2020. [doi]

@inproceedings{LaiJLZM20,
  title = {SynSig2Vec: Learning Representations from Synthetic Dynamic Signatures for Real-World Verification},
  author = {Songxuan Lai and Lianwen Jin and Luojun Lin and Yecheng Zhu and Huiyun Mao},
  year = {2020},
  url = {https://aaai.org/ojs/index.php/AAAI/article/view/5416},
  researchr = {https://researchr.org/publication/LaiJLZM20},
  cites = {0},
  citedby = {0},
  pages = {735-742},
  booktitle = {The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020},
  publisher = {AAAI Press},
  isbn = {978-1-57735-823-7},
}