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Liu L. et al. \"Combination of heterogeneous features for wrist pulse blood flow signal diagnosis via multiple kernel learning.\" IEEE Transactions on Information Technology in Biomedicine 2012."},{"key":"e_1_3_2_1_6_1","volume-title":"from 1-D time series to 2-D matrix","author":"Zhang D.","year":"2018","unstructured":"Zhang , D. , Generalized feature extraction for wrist pulse analysis : from 1-D time series to 2-D matrix .\" ( 2018 ). Zhang, D., et al. \"Generalized feature extraction for wrist pulse analysis: from 1-D time series to 2-D matrix.\" (2018)."},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"crossref","unstructured":"He K. etal \"Deep residual learning for image recognition.\" In Proceedings of the IEEE conference on computer vision and pattern recognition 2016.  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Goodfellow I. et al. \"Generative adversarial nets.\" Advances in neural information processing systems 2014."},{"key":"e_1_3_2_1_12_1","volume-title":"A survey and taxonomy.\" ACM Computing Surveys (CSUR)","author":"Wang Z.","year":"2021","unstructured":"Wang , Z. , She , Q. , & Ward , T. E. \" Generative adversarial networks in computer vision : A survey and taxonomy.\" ACM Computing Surveys (CSUR) , 2021 . Wang, Z., She, Q., & Ward, T. E. \"Generative adversarial networks in computer vision: A survey and taxonomy.\" ACM Computing Surveys (CSUR), 2021."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"crossref","unstructured":"Rabin J. etal \"Wasserstein barycenter and its application to texture mixing.\" International Conference on Scale Space and Variational Methods in Computer Vision 2011.  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