From post

Dynamic Hand Gesture Recognition Using Generalized Time Warping and Deep Belief Networks.

, , , , и . ISVC (2), том 9475 из Lecture Notes in Computer Science, стр. 682-691. Springer, (2015)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

A Kernel-Based Approach for DBS Parameter Estimation., , , , , , и . CIARP, том 10125 из Lecture Notes in Computer Science, стр. 158-166. (2016)Peripheral Nerve Segmentation Using Speckle Removal and Bayesian Shape Models., , , , и . IbPRIA, том 9117 из Lecture Notes in Computer Science, стр. 387-394. Springer, (2015)3D Probabilistic Morphable Models for Brain Tumor Segmentation., , , и . CIARP, том 10657 из Lecture Notes in Computer Science, стр. 314-322. Springer, (2017)Dynamic Hand Gesture Recognition Using Generalized Time Warping and Deep Belief Networks., , , , и . ISVC (2), том 9475 из Lecture Notes in Computer Science, стр. 682-691. Springer, (2015)Bayesian Shape Models with Shape Priors for MRI Brain Segmentation., , и . ISVC (2), том 8888 из Lecture Notes in Computer Science, стр. 851-860. Springer, (2014)Brain Shape Correspondence Analysis Using Functional Maps., , , , , и . ISVC (2), том 13599 из Lecture Notes in Computer Science, стр. 3-12. Springer, (2022)Bayesian Optimization for Fitting 3D Morphable Models of Brain Structures., , и . CIARP, том 10125 из Lecture Notes in Computer Science, стр. 291-299. (2016)Gaussian process dynamical models for multimodal affect recognition., , и . EMBC, стр. 850-853. IEEE, (2016)Brain Shape Correspondence Analysis Using Variational Mixtures for Gaussian Process Latent Variable Models., , , и . IWINAC (1), том 13258 из Lecture Notes in Computer Science, стр. 547-556. Springer, (2022)Bayesian Iterative Closest Point for Shape Analysis of Brain Structures., , , , и . ICPRAM, стр. 920-925. SCITEPRESS, (2023)