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筑波大学　理工情報生命学術院
システム情報工学研究群　情報理工学位プログラム
適　応　情　報　処　理　研　究　室

Selected Papers

  • U. A. Md. Ehsan Ali, Pavodi Ndoyi Maniamfu and Keisuke Kameyama, "Efficient band reduction for hyperspectral imaging with dependency-based segmented principal component analysis," International Journal of Remote Sensing, Vol. 45, No. TBD, pp. TBD, https://doi.org/10.1080/01431161.2024.2408493, 2024.
  • Yuna Park, Tomoumi Takase, Keisuke Kameyama and Masaki Onishi, “Affinity-Weighted RandAugment for Problem-Oriented Augmentation in Image Classification,” International Joint Conference on Neural Networks (IJCNN) 2024, pp. 1-8, https://doi.org/10.1109/IJCNN60899.2024.10651376, June, 2024.
  • Pavodi Ndoyi Maniamfu, U. A. Md. Ehsan Ali and Keisuke Kameyama, “PINN with Antisymmetric RNN for Solving Nonlinear Partial Differential Equations,” International Conference on Scientific Computation and Machine Learning 2024, 5 pages, (Kyoto), Mar. 2024.
  • Pavodi Ndoyi Maniamfu and Keisuke Kameyama, “LSTM-based forecasting using policy stringency and time-varying parameters of the SIR model for COVID-19,” 19th IEEE International Colloquium on Signal Processing and its Applications, pp. 111-116, (Langkawi), https://doi.org/10.1109/CSPA57446.2023.10087773, Mar. 2023.
  • Tzu-Jui Huang and Keisuke Kameyama, “Machine Learning Curriculums Generated by Classifier Ensembles,” 19th IEEE International Colloquium on Signal Processing and its Applications, pp. 117-121, (Langkawi), https://doi.org/10.1109/CSPA57446.2023.10087822, Mar. 2023.
  • Takumi Morikawa and Keisuke Kameyama, “CNN Model Compression by Merit-Based Distillation,” 19th IEEE International Colloquium on Signal Processing and its Applications, pp. 122-127, (Langkawi), https://doi.org/10.1109/CSPA57446.2023.10087390, Mar. 2023 (CSPA Best Paper Award). 
  • U. A. Md. Ehsan Ali and Keisuke Kameyama, "Informative Band Subset Selection for Hyperspectral Image Classification using Joint and Conditional Mutual Information," IEEE Symposium on Computational Intelligence in Remote Sensing (in IEEE SSCI 2022), (Singapore), pp. 573-580, https://doi.org/10.1109/SSCI51031.2022.10022154, Dec. 2022.
  • Takumi Morikawa and Keisuke Kameyama, "Multi-Stage Model Compression using Teacher Assistant and Distillation with Hint-Based Training," Workshop on Pervasive and Resource-constrained AI (PerConAI) part of the 20th IEEE International Conference on Pervasive Computing and Communications (PerCom 2022) (Virtual), pp. 484-490, https://doi.org/10.1109/PerComWorkshops53856.2022.9767229, Mar. 2022.
  • Keita Ogawa and Keisuke Kameyama, "Adaptive Selection of Classifiers for Person Recognition by Iris Pattern and Periocular Image," Proc. 28th International Conference on Neural Information Processing (ICONIP2021), Neural Information Processing. ICONIP 2021. Lecture Notes in Computer Science, vol 13111. Springer, (Bali), pp. 656-667, https://doi.org/10.1007/978-3-030-92273-3_54, Dec. 2021.
  • Yusuke Taguchi, Hideitsu Hino and Keisuke Kameyama, "Pre-Training Acquisition Functions by Deep Reinforcement Learning for Fixed Budget Active Learning," Neural Processing Letters, Vol. 53, pp. 1945-1962, https://doi.org/10.1007/s11063-021-10476-z, Feb. 2021.
  • Yusuke Taguchi, Keisuke Kameyama and Hideitsu Hino, "Active Learning with Interpretable Predictor," International Joint Conference on Neural Networks (IJCNN) (Budapest), pp. 1-8, https://doi.org/10.1109/IJCNN.2019.8852041, July 2019.
  • Shota Utsumi and Keisuke Kameyama, "Parallel Cooperative Ensemble Learning by Adaptive Data Weighting and Error-Correcting Output Codes," LNCS Vol. 11303 (International Conference on Neural Information Processing (ICONIP2018)), (Siem Reap), pp. 673-683, https://doi.org/10.1007/978-3-030-04182-3_59, Dec. 2018.
  • Keisuke Horiuchi and Keisuke Kameyama, "Parameter Density Inheritance Using Kernel Density Estimation for Efficient CNN Learning," Proceedings of 2018 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), pp. 308-313, https://doi.org/10.1109/ISSPIT.2018.8642618, Dec. 2018.
  • Houssem Chatbri, Keisuke Kameyama, Paul Kwan, Suzanne Little and Noel O’Connor, "A Novel Shape Descriptor based on Salient Keypoints Detection for Binary Image Matching and Retrieval," Multimedia Tools and Applications (Springer), https://doi.org/10.1007/s11042-018-6054-x, May 2018.
  • Houssem Chatbri, Kevin McGuinness, Suzanne Little, Jiang Zhou, Keisuke Kameyama, Paul Kwan and Noel O'Connor, "Automatic MOOC video classification using transcript features and convolutional neural networks," ACM Multimedia 2017 - MultiEdTech Workshop, pp. 21-26, https://doi.org/10.1145/3132390.3132393, Oct. 2017.
  • Satoshi Yoshikawa and Keisuke Kameyama, "Keypoint Detection based on Learning to Rank for Robust Image Matching under Resolution Variation," Proceedings of International Workshop on Advanced Image Technology 2017 (IWAIT 2017) (Penang), Paper No. 153, Jan. 2017.
  • Miharu Aizawa and Keisuke Kameyama, "Iris Authentication using Local Spectral Features and their Relational Operations," Proceedings of International Workshop on Advanced Image Technology 2017 (IWAIT 2017) (Penang), Paper No. 138, Jan. 2017.
  • Houssem Chatbri, Kenny Davila, Keisuke Kameyama and Richard Zanibbi, "Shape Matching using Keypoints Extracted From Both the Foreground and the Background of Binary Images," IEEE International Conference on Image Processing Theory, Tools and Applications (IPTA15), pp. 205-210, https://doi.org/10.1109/IPTA.2015.7367128,  Nov. 2015.
  • Keisuke Kameyama, Trung Nguyen Bao Phan and Miharu Aizawa, "Noise-robust Iris Authentication using Local Higher-Order Moment Kernels," LNCS Vol. 9492 (International Conference on Neural Information Processing (ICONIP2015)), pp. 419-427, https://doi.org/10.1007/978-3-319-26561-2_50, Nov. 2015.
  • Houssem Chatbri, Keisuke Kameyama and Paul Kwan, "Towards a Segmentation and Recognition-Free Approach for Content-Based Document Image Retrieval of Handwritten Queries," Asian Conference on Pattern Recognition (ACPR15 Kuala Lumpur), pp. 146-150, https://doi.org/10.1109/ACPR.2015.7486483, Nov. 2015.
  • Houssem Chatbri, Keisuke Kameyama, and Paul Kwan, "A Comparative Study Using Contours and Skeletons as Shape Representations for Binary Image Matching," Pattern Recognition Letters, Vol. 76, No. 1, pp. 59-66, https://doi.org/10.1016/j.patrec.2015.04.007, June 2015.
  • Houssem Chatbri and Keisuke Kameyama, "Document Image Dataset Indexing and Compression Using Connected Components Clustering," IAPR International Conference on Machine Vision and Applications (MVA 2015), pp. 267-270, https://doi.org/10.1109/MVA.2015.7153182, May 2015
  • Houssem Chatbri, Paul Kwan and Keisuke Kameyama, "An Application-Independent and Segmentation-Free Approach for Spotting Queries in Document Images," Proceedings of International Conference on Pattern Recognition (ICPR 2014), pp. 2891-2896, https://doi.org/10.1109/ICPR.2014.498, Aug. 2014.
  • Houssem Chatbri, Paul Kwan and Keisuke Kameyama, "A Modular Approach for Query Spotting in Document Images and Its Optimization Using Genetic Algorithms," Proceedings of the World Congress of Computational Intelligence, pp. 2085-2092, https://doi.org/10.1109/CEC.2014.6900475, Jul. 2014.
  • Houssem Chatbri and Keisuke Kameyama, "Using Scale Space Filtering to Make Thinning Algorithms Robust Against Noise in Sketch Images," Pattern Recognition Letters, Vol. 42, No. 1, pp. 1-10, https://doi.org/10.1016/j.patrec.2014.01.011, June 2014.
  • Wataru Matsumoto and Keisuke Kameyama. "Joint Use of Luminance and Color Invariants In Partial Image Retrieval," Proceedings of 2013 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS) , pp. 602-607, (ISPACS 2013 Outstanding Student Paper Award). https://doi.org/10.1109/ISPACS.2013.6704621, Nov. 2013.
  • Houssem Chatbri, Keisuke Kameyama and Paul Kwan. "Sketch-Based Image Retrieval by Size-Adaptive and Noise-Robust Feature Description," Proceedings of International Conference on Digital Image Computing: Techniques and Applications (DICTA), pp. 469-476, https://doi.org/10.1109/DICTA.2013.6691528, Nov. 2013.
  • Keisuke Kameyama and Wataru Matsumoto. "Composite Color Invariant Feature H' Applied to Image Matching", Lecture Notes in Computer Science (Proc. ICONIP 2013), Vol. 8228, pp. 401-408, https://doi.org/10.1007/978-3-642-42051-1_50, Nov. 2013.
  • Keisuke Kameyama and Trung Nguyen Bao Phan. "Image Feature Extraction and Similarity Evaluation using Kernels for Higher-Order Local Autocorrelation", Lecture Notes in Computer Science (Proc. ICONIP 2013), Vol. 8228, pp. 442-449, https://doi.org/10.1007/978-3-642-42051-1_55, Nov. 2013.
  • Houssem Chatbri and Keisuke Kameyama, "Towards Making Thinning Algorithms Robust against Noise in Sketch Images," Proceedings of International Conference on Pattern Recognition (ICPR2012), pp. 3030-3033, Nov. 2012.
  • Masaki Kobayashi and Keisuke Kameyama, "A Composite Illumination Invariant Color Feature and its Application to Partial Image Matching," IEICE Transactions on Information and Systems, Vol. E95-D, No. 10, pp. 2522-2532, https://doi.org/10.1587/transinf.E95.D.2522, Oct. 2012.
  • Mitsuteru Nakamura, Keisuke Kameyama, Shin Takahashi, Yukio Fukui, Nobuhiko Kitawaki, Su Wei Tan and Yoshikazu Kamiya, "Real-Time Lecture Delivery Connecting Distant Classrooms by Redundant Network Combining a High-Speed Satellite (WINDS) and a Terrestrial Line (JGN2plus)," Proc. 2012 8th IEEE Colloquium on Signal Processing and Its Applications (CSPA 2012) pp. 367-372, (Melaka), March 2012.
  • Paul W. Kwan, Keisuke Kameyama, Junbin Gao, Kazuo Toraichi, "Content-Based Image Retrieval of Cultural Heritage Symbols by Interaction of Visual Perspectives," International Journal of Pattern Recognition and Artificial Intelligence, Vol. 25, No. 5, pp. 643-673, 2011
  • Toru Nozaki and Keisuke Kameyama, "Feature Selection for User-adaptive Content-Based Music Retrieval using Particle Swarm Optimization", Proceedings of 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA 10), pp. 941-946, November, 2010.
  • Shunsuke Sakai, Toru Nozaki and Keisuke Kameyama, "Speaker Verification using Weighted Local MFCC Features Extracted by Minimum Verification Error Learning", Australian Journal of Intelligent Information Processing Systems (Proceedings of ICONIP 2010), pp. 7-12, November, 2010.
  • Shintaro Noguchi and Keisuke Kameyama, "Comparison of Subspace Decomposition and Grouping Methods in Independent Subspace Analysis for Source Separation," 2010 RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing (Honolulu), pp. 21-24, Mar. 2010.
  • Masaki Kobayashi and Keisuke Kameyama, "Partial Image Retrieval using SIFT based on Illumination Invariant Features," International Conference on Multimedia Computing and Information Technology (MCIT 2010) (Sharjah UAE), pp. 33-36, Mar. 2010.
  • Shunsuke Sakai and Keisuke Kameyama, "Text-independent Speaker Verification using Optimized Linear Combination of Local MFCC Features," Proc. SPPRA2010 (Innsbruck) Paper no. 678-063, Feb. 2010.
  • P. W. Kwan, J. Gao, Y. Guo and K. Kameyama, "A Learning Framework for Adaptive Fingerprint Identification using Relevance Feedback," International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24, No. 1, pp. 15-38, Feb. 2010.
  • M. Hisanaga, S. Takahashi, K. Kameyama, Y. Fukui and N. Kitawaki, "WINDS (KIZUNA)-based Collaborative e-Learning Project in Thailand, Malaysia and Japan," Trans. of the Japan Society for Aeronautical and Space Sciences, Aerospace Technology Japan, Vol. 8, No. ists27, pp. Tj_1-Tj-9, Jan. 2010.
  • Makoto Hisanaga, Nobuhiko Kitawaki, Yukio Fukui, Keisuke Kameyama, and Shin Takahashi, "WINDS (Kizuna)-based Collaborative E-Learning Project in Thailand, Malaysia and Japan," Proc. International Symposium on Space Technology and Science (27th ISTS), 2009-j-18, pp.1-9, July 2009.
  • K. Kameyama, "Particle Swarm Optimization - A Survey," IEICE Transactions on Information and Systems, Vol.E92-D, No.7, pp. 1354-1361, Jul. 2009.
  • Nozomi Oka and Keisuke Kameyama, "Relevance Tuning in Content-Based Retrieval of Structurally-Modeled Images using Particle Swarm Optimization," 2009 IEEE Symposium on Computational Intelligence for Multimedia Signal and Vision Processing (CIMSVP), pp. 75-82, Mar. 2009.
  • K. Miyamoto, T. Kamina, T. Sugiyama, K. Kameyama, K. Toraichi and Y. Ohmiya, "A Function Approximation Method for Images with Grading Regions," International Journal of Image and Graphics, Vol. 9, No. 1, pp. 101-119, 2009.
  • Masaki Kobayashi and Keisuke Kameyama, "User-Adaptive Image Clustering using Relevance Feedback for Efficient Content-Based Retrieval," 2008 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2008) , pp. 2683 - 2688, Oct. 2008.
  • Shunsuke Sakai and Keisuke Kameyama, "Content-Based Music Retrieval with Nonlinear Feature Space Transformation using Relevance Feedback," 2008 IEEE International Conference on Systems, Man, and Cybernetics (SMC 2008) , pp. 1379 - 1384, Oct. 2008.
  • Katsuhiko Someya and Keisuke Kameyama, "Locally Adaptive Selection of Parameters in Regularization-Based Denoising Algorithms," Proc. SPPRA2008 (Innsbruck) Paper no. 599-155, Feb. 2008.
  • Keisuke Kameyama, "Comparison of Local Higher-Order Moment Kernel and Conventional Kernels in SVM for Texture Classification," Proc. 14th International Conference on Neural Information Processing (ICONIP’07) , LNCS vol. 4984, pp. 852-860, Springer, Nov. 2007.
  • Mayuko Okayama, Nozomi Oka, and Keisuke Kameyama, "Relevance Optimization in Image Database using Feature Space Preference Mapping and Particle Swarm Optimization," Proc. 14th International Conference on Neural Information Processing (ICONIP’07), LNCS vol. 4985, pp. 608-617, Springer, Nov. 2007.
  • Takashi Mori, Keisuke Kameyama, Yasuhiro Ohmiya, Jia Lee, and Kazuo Toraichi, "Image Resolution Conversion Based on an Edge-Adaptive Interpolation Kernel," Proc. IEEE Pacific Rim Conf. on Comm. Comp. and Sig. Pro. 2007, pp. 497-500, Aug. 2007.
  • K. Kameyama, S.-N. Kim, M. Suzuki, K. Toraichi and T. Yamamoto, "Content-Based Image Retrieval of Kaou Images by Relaxation Matching of Region Features," International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Vol. 14, No. 4, pp. 509-523, Aug. 2006.
  • K. Kameyama, N. Oka and K. Toraichi, "Optimal Parameter Selection in Image Similarity Evaluation Algorithms Using Particle Swarm Optimization," Proc. 2006 IEEE Congress on Evolutionary Computation (Vancouver), pp. 3824-3831, July 2006.
  • Masakazu Higuchi, Shuji Kawasaki, Keisuke Kameyama, Yasuo Morooka and Kazuo Toraichi, "Quality Improvement of MP3 Encoded Audio Reproduction using Fluency Locally Supported Sampling Function for Use in Cell Phones," 7th International Conference on Mobile Data Management (MDM 2006), pp. 142-148, May 2006.
  • K. Sheng, K. Kameyama, K. Toraichi, Y. Mitamura, K. Katagishi, Y. Morooka and Y. Ohmiya, "A Shape-Directed Scaling Method for Fundus Image with Maintenance to Blood-Vessel Shapes and Color Reality," IEEJ Trans. EIS, Vol.125, No.9, pp. 1399-1407, Sep. 2005.
  • K. Kameyama, S-N. Kim, K. Toraichi and T. Yamamoto, "Content-Based Image Retrieval of Kaou Images by Region Characterization and Probabilistic Relaxation," Proc. Modeling Decisions in Artificial Intelligence (MDAI 2005), Paper no.109, (CD-ROM pp. 1-12), July 2005.
  • S. T. Monteiro, K. Uto, Y. Kosugi, N. Kobayashi, E. Watanabe and K. Kameyama : Feature Extraction of Hyperspectral Data for under Spilled Blood Visualization Using Particle Swarm Optimization ; International Journal of Bioelectromagnetism, Vol.7, No.1, pp.1-4, Jul. 2005.
  • K. Kameyama and K. Taga, " Texture Classification by Support Vector Machines with Kernels for Higher-Order Gabor Filtering," Proc. International Joint Conference on Neural Networks 2004 (Budapest), Vol. 4, pp. 3009-3014, July 2004.
  • P. W. H. Kwan, K. Toraichi, H. Kitagawa and K. Kameyama, "Approximate Query Processing for a Content-Based Image Retrieval Method," V. Marik et al.(Eds.): DEXA 2003, LNCS 2736 (Springer) , pp.517-526, Sep. 2003.
  • S-N. Kim, M. Suzuki, K. Kameyama, K. Toraichi and Takashi Yamamoto, "A system for Content-Retrieval and Browsing of Kaou Monogram Images using Contour and Color Characteristics," Proc. 2003 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 844-847, Aug. 2003.
  • K. Taga, K. Kameyama and K. Toraichi, "Regularization of Hidden Layer Unit Response for Neural Networks," Proc. 2003 IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 348-351, Aug. 2003.
  • K. Kameyama and K. Taga, " Layered Neural Network Training with Model Switching and Hidden Layer Feature Regularization," Proc. International Joint Conference on Neural Networks 2003 (Portland), Vol. 3, pp. 2294-2299, July 2003.
  • P. W. H. Kwan, K. Kameyama and K. Toraichi, "On a Relaxation-Labeling Algorithm for Real-time Contour-based Image Similarity Retrieval," Image and Vision Computing Journal, Vol. 21, No. 3, pp. 285-294, Mar. 2003.
  • T. Takahashi, K. Toraichi, K. Kameyama, and K. Nakamura, "A Smooth Interpolation Method For Nonuniform Samples Based on Sampling Functions Composed of Piecewise Polynomials," Proc. IEEE Pacific Rim-Conference on Multimedia 2002 (PCM2002), pp. 417-424, Dec. 2002.
  • K. Kameyama, K. Toraichi and Y. Kosugi, "Constructive Relaxation Matching Involving Dynamical Model Switching and its Application to Shape Matching," International Journal of Image and Graphics, Vol. 2, No. 4, pp. 655-668, Oct. 2002.
  • K. Kameyama, K. Toraichi and Y. Kosugi, "Image Matching based on Relaxation and Model Switching on Contour Characterization," Proc. Joint 1st Int'l Conf. on Soft Computing and Intell. Sys., and 3rd Int'l Symp. on Advanced Intell. Sys. (SCIS & ISIS) 2002, paper 24B4-5, Oct. 2002.
  • P. W. H. Kwan, K. Toraichi, K. Kameyama, F. Kawazoe, and K. Nakamura, "TAST - Trademark Application Assistant," Proc. IEEE International Conference on Image Processing (ICIP) 2002, Vol. 1, pp. 884-887, Sep. 2002.
  • K. Kameyama, K. Toraichi and Y. Kosugi, "Relaxation with Model Switching and its Application to Shape Matching," Proceedings of the 2002 International Joint Conference on Neural Networks (IJCNN 2002), pp. 1564-1569, May 2002.
  • P. W. H. Kwan, K. Kameyama, and K. Toraichi, "Connecting Image Similarity Retrieval with Consistent Labeling by Introducing a Match-All Label," Proceedings of the 10th IEEE International Conference on Fuzzy Systems, Vol. 3, pp. 334-337, Dec. 2001.
  • P. W. H. Kwan, K. Toraichi, K. Wada, K. Kameyama, K. Katagishi, T. Sugiyama, and F. Yoshikawa, "On an Image Contour Compression Method using Compactly Supported Sampling Functions," Proc. 2001 IEEE Pacific Rim Conference on Comm., Comp. and Sig. Pro., pp. 271-274, Aug. 2001.
  • P. W. H. Kwan, K. Kameyama and K. Toraichi, "Trademark Retrieval by Relaxation Matching on Fluency Function Approximated Image Contours," Proc. 2001 IEEE Pacific Rim Conference on Comm., Comp. and Sig. Pro., pp 255-258, Aug. 2001.
  • M. Suzuki, K. Kameyama, K. Toraichi, K. Katagishi, and T. Yamamoto, "On A Kaoh Database System using Fluency Functions based Automatic and Jaggyless Image Coding," Proc. 2001 IEEE Pacific Rim Conference on Comm., Comp. and Sig. Pro., pp 148-151, Aug. 2001.
  • K. Kameyama, K. Toraichi and Y. Kosugi, "A Note on Shape Matching using a Constructive Relaxation Method," Proc. 2001 IEEE Pacific Rim Conference on Comm., Comp. and Sig. Pro., pp. 267-270, Aug. 2001.
  • K. Kameyama and Y. Kosugi, "Neural Network Model Switching for Efficient Feature Extraction," IEICE Trans. on Information and Systems, Vol. E82-D, No. 10, pp. 1372 - 1383, Oct. 1999.
  • K. Kameyama and Y. Kosugi, "Semiconductor Defect Classification using Hyperellipsoid Clustering Neural Networks and Model Switching," Proceedings of International Joint Conference on Neural Networks 1999, Paper No. 569, July 1999.
  • K. Kameyama, Y. Kosugi, T. Okahashi and M. Izumita, "Automatic Defect Classification in Visual Inspection of Semiconductors Using Neural Networks," IEICE Trans. on Information and Systems, Vol. E81-D, No. 11, pp. 1261-1271, Nov. 1998.
  • K. Kameyama and Y. Kosugi, "Model Switching by Channel Fusion for Network Pruning and Efficient Feature Extraction," Proceedings of International Joint Conference on Neural Networks 1998, pp. 1861-1866, May 1998.
  • K. Kameyama, K. Mori and Y. Kosugi, "Texture Segmentation Using A Kernel Modifying Neural Network," IEICE Trans. on Information and Systems, Vol. E80-D, No. 11, pp. 1092-1101, Nov. 1997.
  • M. Kato, T. Sato, K. Kameyama and Y. Kosugi, "Spatial Localization of Stress-perturbing Wave Generated by an Electromagnetic Acoustic Transducer," IEEE Trans. on Ultrasonics, Ferroelectrics and Frequency Control, Vol. 44, No. 5, pp. 1132-1139, Sep. 1997.
  • K. Kameyama and Y. Kosugi, "Spectral and Bispectral Feature Extraction Neural Network for Texture Classification," Proc. SPIE, Statistical and Stochastic Methods in Image Processing II, Vol. 3167, pp. 93 - 103, July 1997.
  • K. Kameyama, K. Mori and Y. Kosugi, "A Neural Network Incorporating Adaptive Gabor Filters for Image Texture Segmentation," Proceedings of 1997 International Conference on Neural Networks (Houston), Vol. 3, pp. 1523-1528, June 1997.
  • Y. Kosugi, Y. Suganami, N. Uemoto, K. Kameyama, M. Sase, T. Momose and J. Nishikawa, "CCE-Based Index Selection for Neuro Assisted MR-Image Segmentation," Proc. IEEE 1996 International Conf. on Image Processing (Lausanne), pp. 249-252, Sep. 1996.
  • K. Kameyama, T. Inoue, I. Yu Demin, K. Kobayashi and T. Sato, "Acoustical Tissue Nonlinearity Characterization Using Bispectral Analysis," Signal Processing (Elsevier), Vol. 53, Issue 2-3, pp. 117-131, Sep. 1996.
  • T. Ogawa, K. Kameyama, R. Kuc and Y. Kosugi, "Source Localization with Network Inversion Using an Answer-in-Weights Scheme," IEICE Transactions on Information and Systems, Vol. E79-D, No. 6, pp. 608-619, Jun. 1996.
  • I. Valova, K. Kameyama and Y. Kosugi, "Image Decomposition by Answer-in-Weights Neural Network," IEICE Trans. on Information and Systems, Vol. E78-D, No. 9, pp. 1221-1224, Sep. 1995.
  • I. Yu. Demin, K. I. Dzhang, K. Kobayashi, K. Kameyama, M. Kato, K. Fudzhi and T. Sato, "Using Low-Frequency Acoustic Waves for Diagnosis of Mild Biological Tissues," Akusticheskii Zhurnal, Vol. 41, No. 3, p. 508, June 1995.
  • M. Kato, T. Sato, K. Kameyama and H. Ninoyu, "Estimation of the Stress Distribution in Metal Using Nonlinear Acoustoelasticity," J. Acoust. Soc. Am., Vol. 98, No. 3, pp. 1496-1504, Mar. 1995.
  • M. Kato, T. Sato, K. Kameyama and H. Ninoyu, "Nondestructive Imaging of Stress Distribution in Metal Using Nonlinear Elasto-Acoustics," Proceedings of 21st International Symposium on Acoustical Imaging (Laguna Beach), Acoustical Imaging (Plenum), Vol. 21, pp. 621-626, Feb. 1994.
  • M. Sakamoto, K. Kameyama, K. Kuwano and T. Sato, "Movement Tracer System Using Non-parallel Multiple Line Detectors and High Order Correlation Analysis," Proc. IAPR Workshop on Machine Vision Applications, pp. 178 - 181, Dec. 1994.
  • K. Fujii, T. Sato, K. Kameyama, T. Inoue, K. Yokoyama and K. Kobayashi, "Imaging System of Precise Hardness Distribution in Soft Tissue in vivo Using Forced Vibration and Ultrasonic Detection," Proceedings of 21st International Symposium on Acoustical Imaging (Laguna Beach), Acoustical Imaging (Plenum), Vol. 21, pp. 253-258, Feb. 1994.
  • S. Hasegawa, K. Hayashi, T. Sato and K. Kameyama, "Simultaneous Imaging System of Three Kinds of Parameters of Nonlinearity for Medical Diagnosis," Proceedings of 21st International Symposium on Acoustical Imaging (Laguna Beach), Acoustical Imaging (Plenum), Vol. 21, pp. 391-397, Feb. 1994.
  • K. Kameyama, T. Sato, S. Hasegawa, K. Hayashi, I. Kodaira, "Information Fusion of Images of Linear and Nonlinear Parameters for Efficient Medical Diagnosis," Abstracts of 18th International Symposium on Ultrasonic Imaging and Tissue Characterization (Arlington), Ultrasonic Imaging, Vol. 16, No. 1, p. 40, Jan. 1994.
  • I. Yu. Demin, T. Sato, Y. Mochida, K. Fujii, K. Y. Jhang, K. Kobayashi, M. Kato and K.Kameyama, "Nonlinear Characteristics of Propagation of Low Frequency Vibration in Soft Tissues and its Measurements Using Bispectral Analysis," Abstracts of 19th International Symposium on Ultrasonic Imaging and Tissue Characterization (Arlington), Ultrasonic Imaging, Vol. 16, No. 1, p. 39, Jan. 1994.
  • K. Kameyama, T. Sato, K. Hayashi, S. Hasegawa and I. Kodaira, "Information Fusion of Images of Linear and Nonlinear Parameters for Efficient Medical Diagnosis, Proceedings of World Federation for Ultrasound in Medicine and Biology (Sapporo), Ultrasound in Medicine and Biology, Vol. 20 supplement 1, p.74, Jan. 1994.
  • Y. Kosugi and K. Kameyama, "Inverse Use of BP Net in Answer-in-Weight Scheme for Arithmetic Calculation," Proc. World Congress on Neural Networks 1993 (Portland), Vol. 3, pp. 462-465, July 1993.
  • K. Hayashi, T. Sato, S. Hasegawa and K. Kameyama, "Ultrasonic Imaging System Combined with Perturbing Waves for Observation of Dynamic and Fine Structure Characteristics of Soft Tissues," Abstracts of 18th International Symposium on Ultrasonic Imaging and Tissue Characterization (Arlington), Ultrasonic Imaging, Vol. 15, No. 2, p. 166, Feb. 1993.
  • K. Fujii, T. Sato, K. Kameyama, K. Kobayashi, "Theoretical Treatment of Propagation Characteristics of Vibration in Soft Tissues and a Method to Obtain Precise Hardness Images in vivo," Abstracts of 18th International Symposium on Ultrasonic Imaging and Tissue Characterization (Arlington), Ultrasonic Imaging, Vol. 15, No. 2, pp. 165 - 166, Feb. 1993.
  • T. Sato, Y. Mochida, K. Fujii, I. Yu. Demin, K. Y. Jhang, K. Kobayashi, M. Kato and K. Kameyama, "Bispectral Analysis Applied for Measurement of Nonlinear Characteristics of Vibration Propagation in Soft Tissues," Proc. of IEEE Signal Processing Workshop on Higher Order Statistics, pp. 369 - 373, May 1993.
  • K. Kameyama, M. Sakamoto, H. Akagi, K. Y. Jhang and T. Sato, "Robot Vision System Using High Order Correlation Analysis," Proc. of IEEE Signal Processing Workshop on Higher Order Statistics, pp. 86 - 90, May 1993.
  • K. Kameyama, M. Iwata, T. Sakai, K. Y. Jhang and T. Sato, "Acousto-Optical Third Order Correlator," Proc. of IEEE Signal Processing Workshop on Higher Order Statistics, pp. 81 - 85, May 1993.
  • K. Kameyama and Y. Kosugi, "Neural Network Pruning by Fusing Hidden Layer Units," Transactions of IEICE, Vol. E74, No. 12, pp. 4198 - 4204, Dec. 1991.
  • Y. Kosugi, K. Kameyama, J. Bita, N. Shitara and K. Takakura, "Neural Network Approaches to the Flowcytometric Data Analysis," Flow cytometry and image analysis for clinical applications, Elsevier (Proc. Int'l. Symp. on Flow Cytometry and Image Analysis for Clinical Applications 1990), pp. 181 - 186, Nov. 1991.
  • K. Kameyama and Y. Kosugi, "Automatic Fusion and Splitting of Artificial Neural Elements in Optimizing the Network Size," Proc. of the International Conference on Systems, Man and Cybernetics 1991, Vol. 3, pp.1633 - 1638, Oct. 1991.
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