2020

  • Yudistira, Novanto, and Takio Kurita. “Correlation Net: Spatiotemporal multimodal deep learning for action recognition.” Signal Processing: Image Communication 82 (2020): 115731.

2019

  • Indraswari, R., Kurita, T., Arifin, A. Z., Suciati, N., & Astuti, E. R. (2019). Multi-projection deep learning network for segmentation of 3D medical images. Pattern Recognition Letters125, 791-797.
  • Yudistira, Novanto, and Takio Kurita. “Deep Packet Flow: Action Recognition via Multiresolution Deep Wavelet Packet of Local Dense Optical Flows.” Journal of Signal Processing Systems91.6 (2019): 609-625.
  • Hidaka, Akinori, Kenji Watanabe, and Takio Kurita. “Sparse discriminant analysis based on estimation of posterior probabilities.” Journal of Applied Statistics (2019): 1-25.

2018

  • Sabri, Motaz, and Takio Kurita. “Facial expression intensity estimation using Siamese and triplet networks.” Neurocomputing313 (2018): 143-154.
  • 井手秀徳, & 栗田多喜夫. (2018). CNN における ReLU 活性化関数に対するスパース正則化の適用と分析. 電子情報通信学会論文誌 D101(8), 1110-1119.
  • Kumagai, Shohei, Kazuhiro Hotta, and Takio Kurita. “Mixture of counting CNNs.” Machine Vision and Applications 29.7 (2018): 1119-1126.
  • Shimono, Eri, et al. “Logistic Regression Analysis for the Material Design of Chiral Crystals.” Chemistry Letters 47.5 (2018): 611-612.

2017

  • Yudistira, Novanto, and Takio Kurita. “Gated spatio and temporal convolutional neural network for activity recognition: towards gated multimodal deep learning.” EURASIP Journal on Image and Video Processing 2017.1 (2017): 85.
  • Sabri, Motaz, and Takio Kurita. “Effect of additive noise for multi-layered perceptron with autoencoders.” IEICE TRANSACTIONS on Information and Systems 100.7 (2017): 1494-1504.
  • SABRI, Motaz, and Takio KURITA. “Improvement of Feature Localization for Facial Expressions by Adding Noise.” International Journal of Affective Engineering 17.1 (2017): 27-37.

  • 野口 祥宏, 嶋田 敬士, マノジ ペレラ, 栗田 多喜夫, “人物画像認識による来場者モニタリング,’’ 精密工学会誌, Vol.80, No.1, pp.89-93, 2014.
  • 田辺 和俊, 栗田 多喜夫, 西田 健次, 鈴木 孝弘、“サポートベクター回帰を用いた158カ国の国債格付けの再現,’’ 情報知識学会誌, Vol. 23 (2013) No. 1, pp. 70-91. 
  • X. Y. Guo, C. Muraki Asano, A. Asano, and T. Kurita, “Modeling the Perception of Visual Complexity in Texture Images,” International Journal of Affective Engineering, vol. 12, no. 2, pp.223-231, 2013. 
  • Tanabe, Kazutoshi, Suzuki, Takahiro, Kurita, Takio, Nishida, Kenji, Lucic, Bono, Amic, Dragan, “Improvement of carcinogenicity prediction performances based on sensitivity analysis in variable selection of SVM models,’’ the Journal of Chemical Information and Modeling (SAR QSAR Environ Res. 2013 Jan 25. DOI:10.1080/1062936X.2012.762425 [Epub ahead of print]) 
  • Keiji Shimada, Yoshihiro Noguchi, and Takio Kuria, “Fast and Robust Smile Intensity Estimation by Cascaded Support Vector Machines,”International Journal of Computer Theory and Engineering, vol.5, no.1, pp.24-30, 2013. 
  • Lei Yang, Akira Asano, Liang Li, Chie Muraki Asano, Takio Kurita, “Multi-structural texture analysis using mathematical morphology, ” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E95-A, No.10, pp.1759-1767, 2012.10. 
  • Xinoying Guo, Chie Muraki Asano, Akira Asano, Takio Kurita, and Liang Li, “ Analysis of the texture characteristics associated with visual complexity perception, Optical Review, Vol.19, no.5, pp.306-314, 2012.10. 
  • Tsuchiya, C., Tanaka, S., Furusho, H., Nishida, K., and Kurita, T.: Real-Time Vehicle Detection using a Single Rear Camera for a Blind Spot Warning System, SAE International Journal of Passenger Cars – Electron. Electr. Syst. 5(1), pp.146-153, 2012. doi:10.4271/2012-01-0293 
  • Kenji Watanabe, Akinori Hidaka, Nobuyuki Otsu, and Takio Kurita, “Automatic Analysis of Composite Physical Signals using Non-negative Factorization and Information Criterion,” PLoS ONE,Vol.7, No.3, e32352, March 2012. 
  • M. S. Kavitha, A. Asano, A. Taguchi, T. Kurita, and M. Sanada, Diagnosis of Osteoporosis on Dental Panoramic Radiographs using Support Vector Machine in Computer-Aided system, BMC Medical Imaging 2012, 12:1 
  • ・Tetsu Matsukawa, and Takio Kurita, “Image representation for generic object recognition using higher-order local autocorrelation features on posterior probability images,” Pattern Recognition (February 2012), 45 (2), pg. 707-719. 
  • Rameswar Debnath, Haruhisa Takahashi and Takio Kurita, “A comparison of SVM-based evolutionary methods for multicategory cancer diagnosis using microarray gene expression data,” Journal of Systemics, Cybernatics and Informatics, vol. 9, no. 6, pp. 63-68, 2011. 
  • 田辺和俊、栗田多喜夫、西田健次、鈴木孝弘、“サポートベクターマシンを用いた企業の信用格付けの予測,” Journal of the Japan Society for Management Information, Vol.20, No.1, pp.23-38, 2011.06. 
  • K.Tanabe, B.Lucic, D.Amic, T.Kurita, M.Kaihara, N.Onodera, T.Suzuki “Prediction of carcinogenicity for diverse chemicals based on substructure grouping and SVM modeling,” Molecular Diversity, Vol.14, No.4, pp.789-802, 2010.11. 
  • T.Matsukawa and T.Kurita, “Extraction of combined features from global/local statistics of visual words using relevant operations,” IEICE Trans. On Information and Systems, Vol.E93-D, No.10, pp.2870-2871, 2010.10.