Shinozaki Takashi
Shinozaki Takashi
Associate Professor, Kindai University
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Cited by
Cited by
Seizure detection by convolutional neural network-based analysis of scalp electroencephalography plot images
A Emami, N Kunii, T Matsuo, T Shinozaki, K Kawai, H Takahashi
NeuroImage: Clinical 22, 101684, 2019
Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network
R Fukuma, T Yanagisawa, M Kinoshita, T Shinozaki, H Arita, ...
Scientific reports 9 (1), 1-8, 2019
Real space observation of three-dimensional network structure of hydrated fibrin gel
A Takahashi, R Kita, T Shinozaki, K Kubota, M Kaibara
Colloid and Polymer Science 281 (9), 832-838, 2003
Autoencoding of long-term scalp electroencephalogram to detect epileptic seizure for diagnosis support system
A Emami, N Kunii, T Matsuo, T Shinozaki, K Kawai, H Takahashi
Computers in biology and medicine 110, 227-233, 2019
Controlling synfire chain by inhibitory synaptic input
T Shinozaki, H Cateau, H Urakubo, M Okada
Journal of the Physical Society of Japan 76 (4), 044806, 2007
Spike suppression in a local cortical circuit induced by transcranial magnetic stimulation
Y Miyawaki, T Shinozaki, M Okada
Journal of computational neuroscience 33 (2), 405-419, 2012
Flexible traffic control of the synfire-mode transmission by inhibitory modulation: nonlinear noise reduction
T Shinozaki, M Okada, AD Reyes, H Cāteau
Physical Review E 81 (1), 011913, 2010
Convolutional neural network with autoencoder-assisted multiclass labelling for seizure detection based on scalp electroencephalography
H Takahashi, A Emami, T Shinozaki, N Kunii, T Matsuo, K Kawai
Computers in Biology and Medicine 125, 104016, 2020
Semi-supervised learning for convolutional neural networks using mild supervisory signals
T Shinozaki
International Conference on Neural Information Processing, 381-388, 2016
Analysis of coagulation of blood in different animal species with special reference to procoagulant activity of red blood cell
M Kaibara, T Shinozaki, R Kita, H Iwata, H Ujiie, K Sasaki, JY Li, ...
Journal of Japanese Society of Biorheology 20 (1), 35-43, 2006
Kobe University, NICT and University of Siegen at TRECVID 2016 AVS Task.
Y Matsumoto, T Shinozaki, K Shirahama, M Grzegorzek, K Uehara
Gap junctions facilitate propagation of synchronous firing in the cortical neural population: a numerical simulation study
T Shinozaki, Y Naruse, H Cāteau
Neural networks 46, 91-98, 2013
Biologically motivated learning method for deep neural networks using hierarchical competitive learning
T Shinozaki
Neural Networks 144, 271-278, 2021
Biologically inspired feedforward supervised learning for deep self-organizing map networks
T Shinozaki
arXiv preprint arXiv:1710.09574, 2017
Impaired inhibition of return during free-viewing behaviour in patients with schizophrenia
K Okada, K Miura, M Fujimoto, K Morita, M Yoshida, H Yamamori, ...
Scientific reports 11 (1), 1-12, 2021
Competitive learning enriches learning representation and accelerates the fine-tuning of CNNs
T Shinozaki
arXiv preprint arXiv:1804.09859, 2018
Generating Images from Sounds Using Multimodal Features and GANs
J Lyu, T Shinozaki, K Amano
Kobe University, NICT and University of Siegen at TRECVID 2017 AVS Task.
Z He, T Shinozaki, K Shirahama, M Grzegorzek, K Uehara
Investigation of color motion using MEG and binocular rivalry stimuli.
T Shinozaki, T Takeda
Neurology & Clinical Neurophysiology: NCN 2004, 108-108, 2004
Feedforward supervised learning for deep neural networks with local competitiveness information
T Shinozaki
IEICE Technical Report; IEICE Tech. Rep. 116 (120), 229-234, 2016
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