| 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 | 94 | 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 | 40 | 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 | 38 | 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 | 13 | 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 | 12 | 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 | 11 | 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 | 10 | 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 | 9 | 2020 |
| Semi-supervised learning for convolutional neural networks using mild supervisory signals T Shinozaki International Conference on Neural Information Processing, 381-388, 2016 | 6 | 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 | 6 | 2006 |
| Kobe University, NICT and University of Siegen at TRECVID 2016 AVS Task. Y Matsumoto, T Shinozaki, K Shirahama, M Grzegorzek, K Uehara TRECVID, 2016 | 5 | 2016 |
| 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 | 5 | 2013 |
| Biologically motivated learning method for deep neural networks using hierarchical competitive learning T Shinozaki Neural Networks 144, 271-278, 2021 | 4 | 2021 |
| Biologically inspired feedforward supervised learning for deep self-organizing map networks T Shinozaki arXiv preprint arXiv:1710.09574, 2017 | 4 | 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 | 3 | 2021 |
| Competitive learning enriches learning representation and accelerates the fine-tuning of CNNs T Shinozaki arXiv preprint arXiv:1804.09859, 2018 | 3 | 2018 |
| Generating Images from Sounds Using Multimodal Features and GANs J Lyu, T Shinozaki, K Amano | 2 | 2018 |
| Kobe University, NICT and University of Siegen at TRECVID 2017 AVS Task. Z He, T Shinozaki, K Shirahama, M Grzegorzek, K Uehara TRECVID, 2017 | 2 | 2017 |
| Investigation of color motion using MEG and binocular rivalry stimuli. T Shinozaki, T Takeda Neurology & Clinical Neurophysiology: NCN 2004, 108-108, 2004 | 2 | 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 | 1 | 2016 |
Ali EmamiUniversity of TokyoVerified email at brain.imi.i.u-tokyo.ac.jp
