フォロー
Shouno Hayaru
タイトル
引用先
引用先
Analysis of function of rectified linear unit used in deep learning
K Hara, D Saito, H Shouno
2015 international joint conference on neural networks (IJCNN), 1-8, 2015
5002015
Analysis of dropout learning regarded as ensemble learning
K Hara, D Saitoh, H Shouno
Artificial Neural Networks and Machine Learning–ICANN 2016: 25th …, 2016
872016
Accuracy of the Bethe approximation for hyperparameter estimation in probabilistic image processing
K Tanaka, H Shouno, M Okada, DM Titterington
Journal of Physics A: Mathematical and General 37 (36), 8675, 2004
402004
A transfer learning method with deep convolutional neural network for diffuse lung disease classification
H Shouno, S Suzuki, S Kido
Neural Information Processing: 22nd International Conference, ICONIP 2015 …, 2015
362015
Development of multiple core-level XPS spectra decomposition method based on the Bayesian information criterion
R Murakami, H Tanaka, H Shinotsuka, K Nagata, H Shouno, H Yoshikawa
Journal of Electron Spectroscopy and Related Phenomena 245, 147003, 2020
212020
Distribution estimation of hyperparameters in Markov random field models
Y Nakanishi-Ohno, K Nagata, H Shouno, M Okada
Journal of Physics A: Mathematical and Theoretical 47 (4), 045001, 2014
212014
Deep feature compression using spatio-temporal arrangement toward collaborative intelligent world
S Suzuki, S Takeda, M Takagi, R Tanida, H Kimata, H Shouno
IEEE Transactions on Circuits and Systems for Video Technology 32 (6), 3934-3946, 2021
202021
Feature representation analysis of deep convolutional neural network using two-stage feature transfer-an application for diffuse lung disease classification
A Suzuki, H Sakanashi, S Kido, H Shouno
arXiv preprint arXiv:1810.06282, 2018
202018
Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval
H Shinotsuka, K Nagata, H Yoshikawa, YI Mototake, H Shouno, M Okada
Science and technology of advanced materials 21 (1), 402-419, 2020
182020
Mosquito larva classification based on a convolution neural network
AS Ortiz, MN Miyatake, H Tünnermann, T Teramoto, H Shouno
Proceedings of the International Conference on Parallel and Distributed …, 2018
162018
Deep convolutional network neocognitron: improved interpolating-vector
K Fukushima, H Shouno
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
162015
Recent studies around the neocognitron
H Shouno
International Conference on Neural Information Processing, 1061-1070, 2007
162007
Training neocognitron to recognize handwritten digits in the real world
K Fukushima, K Nagahara, H Shouno
Proceedings of IEEE International Symposium on Parallel Algorithms …, 1997
161997
Explainable Deep Learning Approach for Multi-Class Brain Magnetic Resonance Imaging Tumor Classification and Localization Using Gradient-Weighted Class Activation Mapping
T Hussain, H Shouno
Information 14 (12), 642, 2023
132023
Correlated topographic analysis: estimating an ordering of correlated components
H Sasaki, MU Gutmann, H Shouno, A Hyvärinen
Machine Learning 92, 285-317, 2013
122013
Bayesian image restoration for medical images using Radon transform
H Shouno, M Okada
Journal of the Physical Society of Japan 79 (7), 074004, 2010
122010
胸部単純 X 線写真における経時的差分画像を用いた結節状陰影の自動検出システムの開発
小田敍弘, 木戸尚治, 庄野逸, 上田克彦
電子情報通信学会論文誌 D 87 (1), 208-218, 2004
122004
Bayesian estimation for XPS spectral analysis at multiple core levels
A Machida, K Nagata, R Murakami, H Shinotsuka, H Shouno, ...
Science and Technology of Advanced Materials: Methods 1 (1), 123-133, 2021
112021
Formation of a direction map by projection learning using Kohonen's self-organization map
H Shouno, K Kurata
Biological cybernetics 85 (4), 241-246, 2001
102001
Detecting seismic electric signals by LVQ based clustering
K Fukuda, M Koganeyama, H Shouno, T Nagao, K Joe
情報処理学会研究報告数理モデル化と問題解決 (MPS) 2001 (63 (2001-MPS-035)), 25-28, 2001
102001
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論文 1–20