Publications

(Japanese papers are omitted)

Journal paper

  • C. N. Ochotorena and Y. Yamashita, “Anisotropic guided filtering,” IEEE Transactions on Image Processing, vol. 29,  pp.1397-1412, 2020.
  • Yukihiko Yamashita and Toru Wakahara, “Affine-transformation and 2D-projection invariant k-NN classification of handwritten characters via a new matching measure,” Pattern Recognition, vol. 52, pp.459-470, April, 2016
    (DOI 10.1016/j.patcog.2015.10.002).
  • Yoshikazu Washizawa, Tatsuya Yokota, and Yukihiko Yamashita, “Multiple kernel learning for quadratically constrained MAP classification,” IEICE Transactions on Information and Systems (letter), vol. E79-D, no. 5, pp.1340–1344, May, 2014.
  • Toru Wakahara and Yukihiko Yamashita, “k-NN classification of handwritten characters via accelerated GAT correlation,” Pattern Recognition vol. 47, no. 3, pp.994-1001, March, 2014.
  • Tatsuya Yokota and Yukihiko Yamashita, “A Quadratically Constrained MAP Classifier Using the Mixture of Gaussians Mode ls as a Weight Function,”
    IEEE Trans. on Neural Networks and Learning Systems vol. 24, no. 7, pp.1127-1140, July, 2013.
  • Nopriadi, Yukihiko Yamashita, “A new approach to a maximum a posteriori-based kernel classification method,” Neural Networks, vol. 33, pp.247-256, Sept., 2012.
  • Hirokazu Yoshino, Chen Dong, Yoshikazu Washizawa, and Yukihiko Yamashita, “Kernel Wiener Filter and its Application to Pattern Recognition,”IEEE Trans. on Neural Networks, vol. 21, no. 11, pp.1719-1730, Nov., 2010.
  • Yoshikazu Washizawa, Yukihiko Yamashita, Toshihisa Tanaka, and Andrzej Cichocki, “Blind extraction of Global Signal form Multi-Channel Noisy Observations,”IEEE Trans. on Neural Networks, vol. 21, no. 9, pp.1472-1481, Sept., 2010.
  • Nasharuddin Zainal, Toshihisa Tanaka, and Yukihiko Yamashita,”Moving picture coding by lapped transform and edge adaptive deblocking filter with zero pruning SPIHT,”IEICE Trans. on Information and Systems, vol. E93-D, no. 6, pp.1608-1617, June, 2010.
  • Joken Son, Naoya Inoue, and Yukihiko Yamashita, “Geometrically local isotropic independence and numerical analysis of the Mahalanobis metric in vector space,”Pattern Recognition Letters, vol. 31, issue 8, pp.709-716, June, 2010.
  • Yoshikazu Washizawa and Yukihiko Yamashita,”Kernel Projection Classifiers with Suppressing Features of Other Classes,”Neural Computation, vol. 18, no. 8, pp.1932-1950, Aug., 2006.
  • Toshihisa Tanaka, Yasutaka Hirasawa, and Yukihiko Yamashita, “Variable-length lapped transform with combination of multiple synthesis filter banks for image coding,” IEEE Trans. Image Processing, vol. 15, no. 1, pp. 81-88, Jan., 2006
  • Toshihisa Tanaka and Yukihiko Yamashita, “The generalized lapped pseudo-biorthogonal transform: Oversampled linear-phase perfect reconstruction filter banks with lattice structures,”IEEE Trans. on Signal Processing, vol.52, no.2, pp.434-446, Feb., 2004.
  • Toshihisa Tanaka, Takateru Saito, and Yukihiko Yamashita, “A time-varying subband transform with projection-based reconstruction,”IEICE Trans. Fundamentals: Special section on digital signal processing, vol. E86-A, no. 8, pp.1935-1941, Aug., 2003.
  • Toshihisa Tanaka and Yukihiko Yamashita, “A biorthogonal transform with overlapping and non-overlapping basis functions for image coding,”IEEE Trans. on Signal Processing, vol. 51, no. 3, pp.732-743, March, 2003.
  • Toshihisa Tanaka and Yukihiko Yamashita, “An adaptive lapped biorthogonal transform and its application in orientation adaptive image coding,”Signal Processing, vol. 82, no. 11, pp.1633-1647, Nov., 2002.
  • Yukihiko Yamashita, “Optimum sampling vectors for Wiener filter noise reduction,”
    IEEE Trans. on Signal Processing, vol. 50, no. 1, pp.58-68, Jan., 2002.
    Toshihisa Tanaka and Yukihiko Yamashita, “Adaptive lapped transforms with overlapping basis functions for image coding,” J. Electronic Imaging, vol. 10, no. 3, pp.706-719, July, 2001.
  • Toshihisa Tanaka and Yukihiko Yamashita, “Vector-embedded Karhunen-Lo\`eve transform and its application in orientation adaptive coding of images,”IEICE Trans. on Fundamentals of Electronics, Communications and Computer Science, vol. E83-A, no. 6, pp.1257-1266, June, 2000.
  • Akira Hirabayashi, Hidemitsu Ogawa, Yukihiko Yamashita, “Admissibility of memorization learning with restpect to projection learning in the presence of noise,”
    IEICE Trans. on Information and Systems, vol. E82-D, no. 2, pp.488-496, Feb., 1999.
  • Yukihiko Yamashita, “New networks for linear programming,”IEICE Trans. on Fundamentals of Electronics, Communications and Computer Science, vol. E81-A, no. 5, pp.931-939, May, 1998.
  • Isao Yamada, Nobuhiko. Ogura, Yukihiko Yamashita, and Kohichi Sakaniwa, “Quadratic optimization of fixed points of nonexpansive mappings in Hilbert space,” Numeral Functional Analysis and Optimization, vol. 19, nos. 1\&2, pp.165-190, March, 1998.
  • Mang Li, Hidemitsu Ogawa, Yukihiko Yamashita, “Paley-Wiener multiresolution analysis and Paley-Wiener wavelet frame,” IEICE Trans. on Fundamentals of Electronics, Communications and Computer Science, vol. E80-A, no. 12, pp.2555-2561, Dec., 1997.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Relative Karhunen-Lo\`eve transform,”
    IEEE Trans. on Signal Processing, vol. 44, no. 2, pp.371-378, Feb., 1996.
    Dawei. Liu, Yukihiko Yamashita, Hidemitsu Ogawa, “Pattern recognition in the presence of noise,” Pattern Recognition, vol. 28, no. 7, pp.989-995, July, 1995.
  • Yuji Koide, Yukihiko Yamashita, and Hidemitsu Ogawa, “A unified theory of the family of projection filters for signal and image estimation,” Systems and Computers in Japan, vol. 26, no. 4, pp.95–105, April., 1995.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Mutual relations among optimum image restoration filters,” Systems and Computers in Japan, vol. 24, no. 6, pp.82–92, Dec., 1993.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Optimum image restoration filter and generalized inverses of operators,” Systems and Computers in Japan, vol. 24, no. 6, pp.72–81, Dec., 1993.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Optimum image restoration and topological invariance,” Systems and Computers in Japan, vol. 24, no. 5, pp.53–63, Nov., 1993.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Properties of averaged projection filter for image restoration,” Systems and Computers in Japan, vol. 23, no. 1, pp.69–78, April, 1992.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Image restoration by averaged projection filter,”  Systems and Computers in Japan, vol. 23, no. 1, pp.79–88, April, 1992.

Conference paper

  • Toru Wakahara and Yukihiko Yamashita, “Stabilized Calculation of Gaussian Smoothing and Its Differentials Using Attenuated Sliding Fourier Transform,” Proceedings of the 2020 25th International Conference on Pattern Recognition (ICPR), pp, 1128-1135, Milan, Italy (online), Jan.~10-15, 2021. (DOI: 10.1109/ICPR48806.2021.9413054)
  • Toru Wakahara and Yukihiko Yamashita, “Image Registration Using 2D Projection Transformation Invariant GPT Correlation,” Proceedings of the Joint 2019 International Workshop on Advanced Image Technology \& International Forum on Medical Imaging in Asia, Singapore, Jan.~ 6–9, pp.110493K-1–6, 2019. (DOI: 10.1117/12.2517185)
  • Carlo Noel Ochotorena, Yukihiko Yamashita, “Multi-scale structure-preserving image filtering,” 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), pp.1–6, Luton, UK, 16-18 Oct.~2017. (DOI: 10.1109/MMSP.2017.8122290)
  • Shizhi Zhang,Toru Wakahara,Yukihiko Yamashita, “Image matching using GPT correlation associated with simplified HOG patterns,” 2017 Seventh International Conference on Image Processing Theory, Tools and Applications (IPTA), pp.1-6, Montreal, QC, Canada, 28 Nov.-1 Dec.~2017. (DOI: 10.1109/IPTA.2017.8310122)
  • Shizhi Zhang, Toru Wakahara and Yukihiko Yamashita, “Theoretical Criterion for Image Matching Using GPT Correlation,” Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), vol. 1, pp. 544-549, Cancun, Mexico, Dec. 4–8, 2016.
  • Toru Wakahara and Yukihiko Yamashita, “Enhanced GPT correlation for 2D projection transformation invariant template matching,” in “Pattern Recognition: 37th German Conference, Proceedings”, pp. 435-445, Aachen, Cermany, Oct. 7-10, 2015 (DOI 10.1007/978-3-319-24947-6_36).
  • Toru Wakahara and Yukihiko Yamashita, “GPT correlation for 2D projection transformation invariant template matching,” Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014), pp.3810–3815, Stockholm, Sweden, Aug. 24–28, 2014.
  • Yukihiko Yamashita and Toru Wakahara, “k-NN Classification of handwritten characters using a new distortion-tolerant matching measure,” Proceedings of the 22nd International Conference on Pattern Recognition (ICPR 2014),
    pp.262–267, Stockholm, Sweden, Aug. 24–28, 2014.
  • Tatsuya Yokota, Toru Wakahara and Yukihiko Yamashita, “Heteroscedastic Gaussian Based Correction term for Fisher Discriminant Analysis and Its Kernel Extension,” Proceedings of the International Joint Conference on Neural Networks,
    no. 1188, Dallas, USA, Aug. 4–9, 2013.
  • Kiung Park and Yukihiko Yamashita, “Image compression by using vector quantization and vector-embedded Karhunen-Lo\`{e}ve Transform,”
    Proceedings of the 28th International Technical Conference on Circuit/Systems, Computers and Communications, (USB), pp.635–638, Yeosu, Korea, June 30–July 3, 2013.
  • Tatsuya Yokota, Andrzej Cichocki, and Yukihiko Yamashita, “Linked PARAFAC/CP tensor decomposition and its fast implementation for group tensor analysis,” Tingwen Huang et al. (Eds.), Proceedings of the 19th International Conference on Neural Information Processing (ICONIP 2012), vol. LNCS 7665, pp.84-91, Springer-Verlag Berlin Heidelberg, Nov. 2012.
  • Toru Wakahara and Yukihiko Yamashita,  “Acceleration of GAT correlation for distortion tolerant image matching,” Proceedings of the 21st International Conference on Pattern Recognition (ICPR 2012), pp.746-749, Tsukuba, Japan, Nov. 11-15, 2012.
  • Naoya Inoue and Yukihiko Yamashita, Simultaneous learning of localized multiple kernels and classifier with weighted regularization, Structural, Syntactic and Statistical Pattern Recognition, G.L. Gimel’ farb et al. (Eds.), (2012 Proceedings of Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2012) and Statistical Techniques in Pattern Recognition (SPR 2012),  Nov. 7-9, Hiroshima, Japan), pp.354-362, Springer Berlin Heidelberg, 2012.
  • Toru Wakahara and Yukihiko Yamashita, “k-NN Classification of Handwritten Characters via Accelerated GAT Correlation,” Proceedings of he 2012 International Conference on Frontiers in Handwriting Recognition (ICFHR-2012), pp.143-148, Bari, Italy, Sept. 18-20, 2012. (DOI 10.1109/ICFHR.2012.225)
  • Nopriadi Nopriadi and Yukihiko Yamashita, “Extended Maximum a Posteriori-based Kernel Classification Trained by Linear Programming (MAPLP) with Adjustment Parameter (MAPLP-P) and Difference-type Objective Function (MAPLP-D),”Proceedings of 18th International Joint Conference on Neural Networks, pp.1-8, Brisbane, Australia, June 10-15, 2012. (DOI 10.1109/IJCNN.2012.6252715)
  • Tatsuya Yokota and Yukihiko Yamashita, “Support Vector Machines with Weighted Regularization,”Proceedings of 18th International Conference on Neural Information Processing, pp.471-480, Shanghai, China, Nov. 14-17, 2011.
  • Toru Wakahara and Yukihiko Yamashita, “Affine-Invariant Recognition of Handwritten Characters via Accelerated KL Divergence Minimization,” Proceddings of 2011 International Conference on Document Analysis and Recognition,pp.1095-1099, Beijing, China, Sept. 18-21, 2011.
  • Tatsuya Yokota and Yukihiko Yamashita, “Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier,”Proceedings of 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, pp. 1-15, New York, USA, Aug. 30-Sept. 3, 2011.
  • Yukihiko Yamashita and Toru Wakahara,”Subspace methods with globally/locally weighted correlation matrix,”Proc. of 20th International Conference on Pattern Recognition (ICPR2010),CD-ROM, Istanbul, Turkey, Aug. 23-26 2010.
  • Toru Wakahara and Yukihiko Yamashita, “Multi-template GAT/PAT correlation for character recognition with a limited quantity of data,” Proc. of 20th International Conference on Pattern Recognition (ICPR2010),CD-ROM, Istanbul, Turkey, Aug. 23-26 2010.
  • Nopriadi and Yukihiko Yamashita, “Maximum a posteriori based kernel classifier trained by linear programming,” Structural, Syntactic and Statistical Pattern Recognition Dit-Yan Yeung, James T.Kwok, Ana Fred, Fabio Roli, and Dick de Ridder (Eds.), (Joint IAPR International Workshops on Structural and Syntactic Pattern Recognition (SSPR 2010) and Statistical Techniques in Pattern Recognition (SPR 2010),  August 18-20, 2010 Proceedings), pp.493-502, Springer Berlin Heidelberg, 2010.
  • Yoshikazu Washizawa, Yukihiko Yamashita, and Andrzej Cichocki, “Blind source extraction using spatio-temporal inverse filter,” Proc. of IEEE International Symposium on Circuits and Systems 2009 (ISCAS 2009),pp.2786-2789, Taipei, Taiwan, May 24-27, 2009.
  • Nasharuddin Zainal and Yukihiko Yamashita, “Moving picture coding by subband transformation and edge adaptive deblocking filter,” Proc. of 2009 RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.451-454, Honolulu, USA, March 1-3, 2009.
  • Son Joken, Naoya Inoue and Yukihiko Yamashita, “Numerical analysis of Mahalanobis metric in vector space,” Proc. of 19th International Conference on Pattern Recognition (ICPR2008), CD-ROM, Tampa, USA, Dec. 8-11 2008.
  • Yoshikazu Washizawa, Yukihiko Yamashita, Toshihisa Tanaka and Andrzej Cichocki,”Blind global source extraction from noisy observations,” 2008 RISP international workshop on nonlinear circuits and signal processing, 2008, Gold coast, Australia, Mar. 5, 2008.
  • Hirokazu Yoshino and Yukihiko Yamashita, “Pattern recognition by kernel Wiener filter,” Proc. of Signal Processing, Pattern Recognition, and Applications (SPPRA 2008), pp.7-12, Innsbruck, Austria, Feb 13-16, 2008.
  • Nasharuddine Zainal, Takashi Ohta, and Yukihiko Yamashita, “Moving picture coding by wavelet transform and edge adaptive deblocking filter,” Proc. of the 2007 International Conference on Image Processing, Computer Vision, \& Pattern Recognition, Las Vegas, USA, June 25-28, 2007.
  • Yoshikazu Washizawa, Yukihiko Yamashita, Toshihisa Tanaka and Andrzej Cichocki, “Extraction of steady state visually evoked potential signal and estimation of distribution map from EEG data,” Proc. of 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Lyon, France, pp. 5449-5451, Aug. 23-26, 2007.
  • Naoya Koide and Yukihiko Yamashita,”Asymmetric kernel method and its application to Fisher’s discriminant,” Proc. of 18th International Conference on Pattern Recognition (ICPR2006),Vol. 2, pp.820-824, HongKong China, Aug. 20-24, 2006.
  • Yoshikazu Washizawa and Yukihiko Yamashita, “Non-linear Wiener filter in reproducing kernel Hilbert space,” Proc. of 18th International Conference on Pattern Recognition (ICPR2006), Vol. 1, pp.967-970, HongKong China, 20-24 Aug. 2006.
  • Yukihiko Yamashita, Mariko Numakami, and Naoya Inoue, “Maxwell normal distribution in a Manifold and Mahalanobis metric,” Structural, Syntactic and Statistical Pattern Recognition Dit-Yan Yeung, James T.Kwok, Ana Fred, Fabio Roli, and Dick de Ridder (Eds.), (Joint IAPR International Workshops SSPR2006 and SPR2006, Hong Kong, China, August 17-19, 2006 Proceedings), pp.604-612, Springer Berlin Heidelberg, 2006.
  • Yoshikazu Washizawa, Yukihiko Yamashita, “Kernel Sample Space Projection Classifier for Pattern Recognition,” Proc. of 17th International Conference on Pattern Recognition (ICPR’04), Vol. 2, pp. 435-438, Cambridge UK, August 23-26, 2004.
  • Yoshikazu Washizawa, Kenji Hikida, Toshihisa Tanaka, and Yukihiko Yamashita, “Kernel relative component analysis for pattern recognition,” Ana Fred, Terry Caelli, Robert P.W. Duin, Aur\'{e}lio Campilho, Dick de Ridder (Eds.), Structural, Syntactic and Statistical Pattern Recognition (Joint IAPR International Workshops SSPR2004 and SPR2004,  Lisbon, Portugal, August 18-20, 2004 Proceedings), pp.1105-1113, Springer Berlin Heidelberg, 2004.
  • Toshihisa Tanaka, Takateru Saito, and Yukihiko Yamashita, “Projection-based time-varying subband image coding,” Proc. of 2003 IEEE International Conference on Image Processing (ICIP 2003), vol. III, pp. 201-204, Barcelona, Spain, 14-17, Sept. 2003.
  • Toshihisa Tanaka, Yasutaka Hirasawa, and Yukihiko Yamashita, “A novel class of variable-length lapped transform for image coding,” Proc. of 2003 IEEE International Conference on Image Processing (ICIP 2003), vol. I, pp.649-652, Barcelona, Spain, 14-17, Sept. 2003.
  • Toshihisa Tanaka and Yukihiko Yamashita, “Noise robust oversampled linear phase perfect reconstruction filter bank with a lattice structure,” Proc. of 2002 IEEE International Conference on Image Processing (ICIP 2002), CD-ROM, Rochester, NY, USA, Sept. 22-25, 2002.
  • Toshihisa Tanaka and Yukihiko Yamashita, “The generalized lapped pseudo-biorthogonal transform,” Proc. of 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2002), vol. II, pp. 1273-1276, Orlando, May 13-17, 2002.
  • Toshihisa Tanaka and Yukihiko Yamashita, “The orientation adaptive lapped biorthogonal transform for efficient image coding,” Proc. of 2001 IEEE International Conference on Image Processing (ICIP 2001), vol. III, pp. 214-217, Thessaloniki, Greece, Oct. 7-10, 2001.
  • Toshihisa Tanaka and Yukihiko Yamashita “A biorthogonal transform with overlapping and non-overlapping basis functions for image coding,” Proc. of 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2001), Salt Lake City, USA, vol. III, pp.1705-1708, May 7-11, 2001.
  • Kenichi Maruko and Yukihiko Yamashita, “BISC (Bus Instruction Set Computer) architecture and BISC-1,” Proc. of 2000 International Technical Conference on Circuits/Systems, Computers, and Communications (ITC-CSCC 2000), vol. 2 , pp. 935-938, Tokushima, Japan, July 9-12, 2001.
  • Toshihisa Tanaka and Yukihiko Yamashita, “The orientation adaptive lapped orthogonal transform for image coding,” Proc. of 2000 IEEE International Conference on Image Processing (ICIP 2000), vol. III, pp. 829-832, Vancouver, Canada, Sept. 10-13, 2000.
  • Toshihisa Tanaka and Yukihiko Yamashita, “An iterative deblocking method using 2-D directional FIR filters,” Proc. of 2000 International Technical Conference on Circuits/Systems, Computers, and Communications vol. 1, pp. 46-49, Pusan, July 11-13, 2000.
  • Toshihisa Tanaka and Yukihiko Yamashita, “Image Coding using vector-embedded Karhunen-Lo\`eve transform,” Proc. of 1999 IEEE International Conference on Image Processing, Kobe, Japan, vol. 2, pp. 482-486, Oct. 24-28, 1999.
  • Ryoichi Abe, Hirofumi Isobe, and Yukihiko Yamashita, “Simulator in a virtual space for autonomous robot and vehicle,” Proc. of 1999 IEEE International Conference on System, Man, and Cybernetics, vol. 6, Tokyo, Japan, pp.625-630, Oct. 12-15, 1999.
  • Yasuyuki Ikeno, Yukihiko Yamashita, and Hidemitsu Ogawa, “Relative Karhunen-Lo\`eve transform method for pattern recognition,” Proc. of the 14th International Conference on Pattern Recognition, vol. 2, Brisben, Austraria, pp.1031-1033, Aug. 25-29, 1998.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Relative Karhunen-Lo\`eve transform and an optimum sampling,” Proc. of the 4th International Conference on Optimization: Techniques and Applications, vol. 2, Perth, Austraria, pp.1009-1016, July. 1-3, 1998.
  • Isao Yamada, Nobuhiko. Ogura, Yukihiko Yamashita and Kohichi Sakaniwa, “An Optimal fixed point theorm for nonexpansive operator and its application to set theoritic singal estimation – Optimization with inconsistent convex constraints – ,” Proc. of 1996 International Symposium on Information Theory and its Application, pp.736-742, Oct. 1997.
  • Yukihiko Yamashita, “Image compression by Weighted Karhunen-Lo\`eve operator,” Proc. of the 13th International Conference on Pattern Recognition, vol. B, Vienna, Autria, pp.636-640, Aug. 25-29, 1996.
  • Yukihiko Yamashita and Hidemitsu Ogawa, “Relative Karhunen-Lo\`eve operator,” Proc. of the 12th International Conference on Pattern Recognition, vol. 3, Jerusalem, Israel, pp.168-170, Oct. 9-13, 1994.
  • Yukihiko Yamashita, “Methods of convex projections with optimum condition,” The 2nd International Symposium on Inverse Problems in Engineering Sciences, Oosaka, pp.C43-C44, July 27-30, 1994.