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Tomoumi Takase

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Neural Networks : the Official Journal of the International Neural Network Society|October 8, 2024
Optimal layer selection for latent data augmentationTomoumi Takase, Ryo Karakida
Neural Networks : the Official Journal of the International Neural Network Society|March 2, 2018
Effective neural network training with adaptive learning rate based on training lossTomoumi Takase, Satoshi Oyama, Masahito Kurihara
Neural Computation|April 14, 2018
Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic OptimizationTomoumi Takase, Satoshi Oyama, Masahito Kurihara
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 11, 2021
Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer MappingSuguru Kanoga, Tomoumi Takase, Takayuki Hoshino, et al.
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Showing results (1-10 of 4) with videos related to

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Pageof 1
Neural Networks : the Official Journal of the International Neural Network Society|October 8, 2024
Optimal layer selection for latent data augmentationTomoumi Takase, Ryo Karakida
Neural Networks : the Official Journal of the International Neural Network Society|March 2, 2018
Effective neural network training with adaptive learning rate based on training lossTomoumi Takase, Satoshi Oyama, Masahito Kurihara
Neural Computation|April 14, 2018
Why Does Large Batch Training Result in Poor Generalization? A Comprehensive Explanation and a Better Strategy from the Viewpoint of Stochastic OptimizationTomoumi Takase, Satoshi Oyama, Masahito Kurihara
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|December 11, 2021
Time-domain Mixup Source Data Augmentation of sEMGs for Motion Recognition towards Efficient Style Transfer MappingSuguru Kanoga, Tomoumi Takase, Takayuki Hoshino, et al.
Pageof 1