{"id":172,"date":"2023-03-27T14:16:03","date_gmt":"2023-03-27T05:16:03","guid":{"rendered":"https:\/\/wps.itc.kansai-u.ac.jp\/s-yos\/?page_id=172"},"modified":"2026-04-04T12:40:56","modified_gmt":"2026-04-04T03:40:56","slug":"publications","status":"publish","type":"page","link":"https:\/\/wps.itc.kansai-u.ac.jp\/s-yos\/publications\/","title":{"rendered":"\u7814\u7a76\u696d\u7e3e"},"content":{"rendered":"\n
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  1. S. Fuchigami, R. Yoshida, S. Yoshida, and M. Muneyasu: Class Imbalanced Multiclass Classification of Harmful Posts in Social Networks Based on Heterogeneous Graphs, IEICE Trans. Fundamentals, vol. E109-A, no. 6, pp. **-**, Jun. 2026 DOI:<\/strong> 10.1587\/transfun.2025SMP0005<\/a><\/li>\n\n\n\n
  2. T. Abe, S. Yoshida, and M. Muneyasu: Generalized Distillation with Multi-Task Graph Neural Networks for Early Fake News Detection, IEICE Trans. Fundamentals, vol. E109-A, no. 6, pp. **-**, Jun. 2026 DOI:<\/strong> 10.1587\/transfun.2025SMP0006<\/a><\/li>\n\n\n\n
  3. S. Nakano, K. Iwasaki, M. Muneyasu, S. Yoshida, M. Okuda, N. Dewake, N. Yoshinari, and K. Uchida: A New Detector of Calcification Regions in Dental Panoramic Radiographs, IEICE Trans. Fundamentals, vol. E109-A, no. 6, pp. **-**, Jun. 2026 DOI:<\/strong> 10.1587\/transfun.2025SML0004<\/a><\/li>\n\n\n\n
  4. K. Nishimoto, M. Muneyasu, and S. Yoshida: Data Detection from Images on Curved Surfaces in Data Embedding  to Printed Images Using Auxiliary Lines and Its Implementation, IEICE Trans. Fundamentals, vol. E109-A, no. 6, pp. **-**, Jun. 2026 DOI:<\/strong> 10.1587\/transfun.2025SML0002<\/a><\/li>\n\n\n\n
  5. H. Okada, S. Yoshida, and M. Muneyasu : Disentangling Shared and Specific Representations for Multimodal Cross-Domain Recommendation via Cosine-Based Regularization, IEICE Trans. Information and Systems, vol. E109-D, no. 7, pp. **-**, Jul. 2026 DOI:<\/strong> 10.1587\/transinf.2025DAL0002<\/a><\/li>\n\n\n\n
  6. S. Yamamoto, S. Yoshida, and M. Muneyasu: Feature Space-Preserving Machine Unlearning for Robust Image Classification with Noisy Labels, IEEE Access, vol. 14, pp. 45449-45463, Mar. 2026, DOI<\/strong>: 10.1109\/ACCESS.2026.3676403<\/a><\/li>\n\n\n\n
  7. S. Yoshida: Community-aware Two-stage Diversification for Social Media User Recommendation with Graph Neural Networks, Information, vol. 17, no. 1, Jan. 2026 DOI:<\/strong> 10.3390\/info17010029<\/a><\/li>\n\n\n\n
  8. T. Horihata, S. Yoshida, and M. Muneyasu: Domain Adaptation across Geographic Regions through Region-Specific Feature Learning and Distribution Matching, IEEE Access, vol. 13 pp. 138718-138732, Aug. 2025, DOI<\/strong>: 10.1109\/ACCESS.2025.3596221<\/a><\/li>\n\n\n\n
  9. R. Yoshida, S. Yoshida, and M. Muneyasu: MAHGA: Multi-Aspect Heterogeneous Graph Analysis for Harmful Speech Detection on Social Networks, IEEE Access, vol. 13, pp. 106673-106689, Jun. 2025, DOI<\/strong>: 10.1109\/ACCESS.2025.3581214<\/a><\/li>\n\n\n\n
  10. T. Sugiyama, S. Yoshida, and M. Muneyasu: Joint Modeling of Prediction and Behavioral Patterns for Reliable Recommendation With Implicit Feedback, IEEE Access, vol. 13, pp. 49788-49800, Mar. 2025, DOI<\/strong>: 10.1109\/ACCESS.2025.3552102<\/a><\/li>\n\n\n\n
  11. R. Yoshida, S. Yoshida, and M. Muneyasu: Embedding Learning with Relational Heterogeneous Information in Social Network Posts to Detect Malicious Behavior, IEICE Trans. Fundamentals, vol. E108-A, no. 3, pp. 295-303, Mar. 2025 DOI:<\/strong> 10.1587\/transfun.2024SMP0004<\/a><\/li>\n\n\n\n
  12. S. Yoshida, N. Yatoh, and M. Muneyasu: Aesthetic Evaluation of Chinese Calligraphy Using TabNet: Interpretability and Novel Features for Improved Accuracy, IEICE Trans. Fundamentals, vol. E108-A, no. 3, pp. 357-361, Mar. 2025 DOI:<\/strong> 10.1587\/transfun.2024SML0003<\/a><\/li>\n\n\n\n
  13. S. Takano, M. Muneyasu, S. Yoshida, A. Asano, N. Dewake, N. Yoshinari, and K. Uchida: Application of Adversarial Training in the Detection of Calcification Regions from Dental Panoramic Radiographs, IEICE Trans. Fundamentals, vol. E108-A, no. 3, pp. 352-356, Mar. 2025 DOI:<\/strong> 10.1587\/transfun.2024SML0002<\/a><\/li>\n\n\n\n
  14. T. Abe, S. Yoshida, and M. Muneyasu: Dynamic Graph Convolutional Network with Time-Series-Aware Structural Feature Extraction for Fake News Detection, ITE Transactions on Media Technology and Applications, vol. 13, no. 1, pp. 106-118, Jan. 2025 DOI:<\/strong> 10.3169\/mta.13.106<\/a><\/li>\n\n\n\n
  15. R. Fukunaga, S. Yoshida, R. Higashimoto, and M. Muneyasu: Enhancing Robustness to Noisy Labels by Explicit Disentanglement of Similar Classes in Feature Space using Contrastive Learning, ITE Transactions on Media Technology and Applications, vol. 13, no. 1, pp. 91-105, Jan. 2025 DOI:<\/strong> 10.3169\/mta.13.91<\/a><\/li>\n\n\n\n
  16. T. Sugiyama, S. Yoshida, and M. Muneyasu: DRGNN: Disentangled Representation Graph Neural Network for Diverse Category-level Recommendations, Pattern Recognition Letters, vol. 186, pp. 78-84, Oct. 2024 DOI:<\/strong> 10.1016\/j.patrec.2024.09.008<\/a><\/li>\n\n\n\n
  17. R. Higashimoto, S. Yoshida, and M. Muneyasu : ConfidentMix: Confidence-guided Mixup for Learning With Noisy Labels, IEEE Access, vol. 12, pp. 58519-58531, Apr. 2024 DOI:<\/strong> 10.1109\/ACCESS.2024.3393440<\/a><\/li>\n\n\n\n
  18. K. Soga, S. Yoshida, and M. Muneyasu: Graph-Based Interpretability for Fake News Detection through Topic- and Propagation-Aware Visualization, Computation, vol. 12, no. 4, Apr. 2024 DOI:<\/strong> 10.3390\/computation12040082<\/a><\/li>\n\n\n\n
  19. R. Higashimoto, S. Yoshida, and M. Muneyasu : CRAS: Curriculum Regularization and Adaptive Semi-Supervised Learning with Noisy Labels, Applied Sciences, vol. 14, no. 3, Jan. 2024 DOI:<\/strong> doi.org\/10.3390\/app14031208<\/a><\/li>\n\n\n\n
  20. R. Higashimoto, S. Yoshida, T. Horihata, and M. Muneyasu : Unbiased Pseudo-Labeling for Learning with Noisy Labels, IEICE Trans. Information and Systems, vol. E107-D, no. 1, pp. 44-48, Jan. 2024 DOI:<\/strong> 10.1587\/transinf.2023MUL0002<\/a><\/li>\n\n\n\n
  21. K. Soga, S. Yoshida, and M. Muneyasu: Exploiting Stance Similarity and Graph Neural Networks for Fake News Detection, Pattern Recognition Letters, vol. 177, pp. 26-32, Jan. 2024 DOI:<\/strong> 10.1016\/j.patrec.2023.11.019<\/a><\/li>\n\n\n\n
  22. H. Shimoyama, S. Yoshida, T. Fujita, and M. Muneyasu : U-Net Architecture for Ancient Handwritten Chinese Character Detection in Han Dynasty Wooden Slips, IEICE Trans. Fundamentals, vol. E106-A, no. 11, pp.1406-1415, Nov. 2023 DOI:<\/strong> 10.1587\/transfun.2023SMP0007<\/a><\/li>\n\n\n\n
  23. M. Yasuda, S. Yoshida, and M. Muneyasu : New Performance Evaluation Method for Data Embedding Techniques for Printed Images Using Mobile Devices Based on a GAN, IEICE Trans. Fundamentals, vol. E106-A, no.3, pp. 481-485, Mar. 2023 DOI:<\/strong> 10.1587\/transfun.2022SML0003<\/a><\/li>\n\n\n\n
  24. H. Takeda, S. Yoshida and M. Muneyasu : Training Robust Deep Neural Networks on Noisy Labels Using Adaptive Sample Selection with Disagreement, IEEE Access, vol. 9, pp. 141131-141143, Oct. 2021 DOI: <\/strong>10.1109\/ACCESS.2021.3119582<\/a><\/li>\n\n\n\n
  25. S. Yoshida, M. Muneyasu, T. Ogawa, and M. Haseyama : Heterogenerous-Graph-Based Video Search Reranking Using Topic Relevance, IEICE Trans. Fundamentals, vol. E103-A, no.12, pp. 1529-1540, Dec. 2020 DOI:<\/strong> 10.1587\/transfun.2020SMP0023<\/a><\/li>\n\n\n\n
  26. T. Fujii, S. Yoshida and M. Muneyasu : Video Search Reranking with Relevance Feedback Using Visual and Textual Similarities, IEICE Trans. Fundamentals, vol. E102-A, no.12, pp. 1900-1909, Dec. 2019 DOI:<\/strong> 10.1587\/transfun.E102.A.1900<\/a><\/li>\n\n\n\n
  27. S. Oohara, M. Muneyasu, S. Yoshida and M. Nakashizuka : Image Regularization with Total Variation and Optimized Morphologocal Gradient Priors, IEICE Trans. Fundamentals, vol. E102-A, no.12, pp. 1920-1924, Dec. 2019 DOI:<\/strong> 10.1587\/transfun.E102.A.1920<\/a><\/li>\n\n\n\n
  28. S. Yoshida, T. Ogawa, M. Haseyama and M. Muneyasu : Graph-Based Video Search Reranking with Local and Global Consistency Analysis, IEICE Trans. Inf. & Syst., vol. E101-D, no.5, pp. 1430-1440, May 2018 DOI:<\/strong> 10.1587\/transinf.2017EDP7277<\/a><\/li>\n\n\n\n
  29. M. Muneyasu, N. Jinda, Y. Moritani and S. Yoshida : Data Extraction Method from Printed Images with Different Formats, IEICE Trans. Fundamentals, vol. E100-A, no.11, pp. 2355-2357, Nov. 2017 DOI:<\/strong> 10.1587\/transfun.E100.A.2355<\/a><\/li>\n\n\n\n
  30. \u5409\u7530 \u58ee\uff0c\u5c0f\u5ddd \u8cb4\u5f18\uff0c\u9577\u8c37\u5c71\u7f8e\u7d00 : \u6b4c\u8b21\u756a\u7d44\u306b\u304a\u3051\u308b\u6620\u50cf\u306e\u69cb\u9020\u306b\u6ce8\u76ee\u3057\u305f\u30b7\u30fc\u30f3\u5206\u5272\u624b\u6cd5, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8ad6\u6587\u8a8c(D), vol.J97-D, no.7, pp. 1177-1188, 2014<\/li>\n\n\n\n
  31. S. Yoshida, H. Okada, T. Ogawa, and M. Haseyama : A Method for Improving SVM-based Image Classification Performance Based on a Target Object Detection Scheme, ITE Transactions on Media Technology and Applications, vol.1, no. 3, pp.237-243, 2013 DOI:<\/strong> 10.3169\/mta.1.237<\/a><\/li>\n<\/ol>\n\n\n\n
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    1. R. Fukunaga, S. Yoshida, and M. Muneyasu: ACD-U: Asymmetric Co-teaching with Machine Unlearning for Robust Learning with Noisy Labels, arXiv preprint, arXiv:2603.07166, Mar. 2026, DOI<\/strong>: 10.48550\/arXiv.2603.07166<\/a><\/li>\n<\/ol>\n\n\n\n
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      1. \u5409\u7530\u3000\u58ee\uff1a\u30ce\u30a4\u30b8\u30fc\u30e9\u30d9\u30eb\u3092\u7528\u3044\u305f\u753b\u50cf\u5206\u985e, IEICE Fundamentals Review, vol. 18, no. 2, pp. 147-157, Oct. 2024 DOI:<\/strong> 10.1587\/essfr.18.2_147<\/a><\/li>\n\n\n\n
      2. \u5409\u7530\u3000\u58ee\uff1a\u52d5\u753b\u50cf\u691c\u7d22\u306e\u305f\u3081\u306e\u9069\u5408\u6027\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u3092\u7528\u3044\u305f\u30ea\u30e9\u30f3\u30ad\u30f3\u30b0\uff0c\u96fb\u6c17\u5b66\u4f1a\u30fb\u30c7\u30a3\u30b8\u30bf\u30eb\u4fe1\u53f7\u51e6\u7406\u30b7\u30b9\u30c6\u30e0\u6700\u9069\u5316\u6280\u8853\u8abf\u67fb\u5c02\u9580\u59d4\u54e1\u4f1a \u7de8\uff1a\u30c7\u30a3\u30b8\u30bf\u30eb\u4fe1\u53f7\u51e6\u7406\u306b\u304a\u3051\u308b\u30b7\u30b9\u30c6\u30e0\u6700\u9069\u5316\u6280–\u57fa\u790e\u6280\u8853\u304b\u3089\u97f3\u58f0\u30fb\u97f3\u97ff\u4fe1\u53f7\u51e6\u7406\uff0c\u7523\u696d\u5fdc\u7528\u3068\u60c5\u5831\u30b7\u30b9\u30c6\u30e0\u307e\u3067-\u7b2c12\u7ae0\uff0c\u30aa\u30fc\u30e0\u793e\uff0cpp.237-257, 2021<\/li>\n<\/ol>\n\n\n\n
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        1. S. Takano, M. Muneyasu, and S. Yoshida : A New Image Watermarking Method Using Adversarial Perturbations, Proc. 2022 International Workshop on Smart Info-Media Systems in Asia, online, Sept. 15\u201316, SISA-AVM-01, 2022<\/li>\n\n\n\n
        2. H. Matsumoto, S. Yoshida and M. Muneyasu : Flexible Framework to Provide Explainability for Fake News Detection Methods on Social Media, Proc. 2022 IEEE 11th Global Conference on Consumer Electronics, Osaka, Japan, Oct. 18\u201321, pp.421-422, 2022<\/li>\n\n\n\n
        3. K. Soga, S. Yoshida and M. Muneyasu : Propagation-Based Fake News Detection Using a Combination of Different Content Features, Proc. 2022 IEEE 11th Global Conference on Consumer Electronics, Osaka, Japan, Oct. 18\u201321, pp. 411-412, 2022 (IEEE GCCE 2022 Excellent Student Poster Award Silver Prize)<\/mark><\/li>\n\n\n\n
        4. R. Higashimoto, S. Yoshida and M. Muneyasu : A Robust Learning Framework Using Self-supervised Learning for Learning with Noisy Labels, Proc. 2022 IEEE 11th Global Conference on Consumer Electronics, Osaka, Japan, Oct. 18\u201321, pp. 409-410, 2022<\/li>\n\n\n\n
        5. F. Kotegawa, M. Muneyasu, and S. Yoshida : Method of Extracting Data from Images on a Curved Surface in Data Embedding to Printed Images Using Mobile Devices, Proc. 2021 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), Hualien, Taiwan, Nov. 16\u201319, O2-4, 2021<\/li>\n\n\n\n
        6. T. Murano, M. Muneyasu, S. Yoshida, K. Chamnongthai, A. Asano, and K. Uchida : New Method of Detecting Calcification Regions in Dental Panoramic Radiographs Based on U-PraNet, Proc. 2021 20th International Symposium on Communication and Information Technologies (ISCIT), Tottori, Japan, Oct. 20\u201322, W1-3, pp.11-14, 2019<\/li>\n\n\n\n
        7. H. Matsumoto, S. Yoshida and M. Muneyasu : Propagation-Based Fake News Detection Using Graph Neural Networks with Transformer, Proc. 2021 IEEE 10th Global Conference on Consumer Electronics, Kyoto, Japan, Oct. 12\u201315, pp.19-20, 2021<\/li>\n\n\n\n
        8. M. Yasuda, M. Muneyasu, and S. Yoshida : Method of Generating Pseudo-Captured Images to Evaluate the Performance of Data Embedding Techniques for Printed Images Using Mobile Devices, Proc. 2021 International Workshop on Smart Info-Media Systems in Asia, online, Sept. 20\u201322, pp.28-33, 2021<\/li>\n\n\n\n
        9. T. Murano, M. Muneyasu, S. Yoshida, K. Chamnongthai, A. Asano, K. Uchida, N. Dewake, Y. Ishioka, and N. Yoshinari : Detection of Calcification Regions from Dental Panoramic Radiographs Based on Semantic Segmentation Using Deep Learning, Proc. 2021 International Workshop on Smart Info-Media Systems in Asia, online, Sept. 20\u201322, pp.122-127, 2021<\/li>\n\n\n\n
        10. S. Yoshida, T. Fujita and M. Muneyasu : A Character-region-aware Deep Network for Chinese Character Detention from Wood Slips of the Han Period, Proc. 2020 International Workshop on Smart Info-Media Systems in Asia, Online, Dec. 18\u201319, pp.18-23, 2020<\/li>\n\n\n\n
        11. M. Amami, M. Muneyasu and S. Yoshida : Data Extraction from Printed Data-Embedded Image Using Projectors, Proc. 2020 International Workshop on Smart Info-Media Systems in Asia, Online, Dec. 18\u201319, pp.12-17, 2020<\/li>\n\n\n\n
        12. M. Shiiba, M. Muneyasu and S. Yoshida : New Data Embedding and Detecting Method for Printed Image, Proc. 2019 IEEE 8th Global Conference on Consumer Electronics, Osaka, Japan, Oct. 15\u201318, pp.223-224, 2019<\/li>\n\n\n\n
        13. H. Takeda, S. Yoshida and M. Muneyasu : Learning from Noisy Labeled Data Using Symmetric Cross-Entropy Loss for Image Classification, Proc. 2020 IEEE 9th Global Conference on Consumer Electronics, Kobe, Japan, Oct. 13\u201316, pp.770-772, 2020<\/li>\n\n\n\n
        14. S. Oohara, H. Oka, M. Muneyasu, S. Yoshida, and M. Nakashizuka : Image Regularization with Morphological Gradient Priors Using Optimal Structuring Element for Each Pixel, Proc. 2019 International Symposium on Intelligent Signal Processing and Communication Systems, Taipei, Taiwan, Dec. 3\u20136, O22-1, 2019<\/li>\n\n\n\n
        15. T. Nishikawa, M. Muneyasu, Y. Nishida, S. Yoshida and K. Chamnongthai : Data Retrieval from Printed Image Using Image Features and Data Embedding, Proc. 2019 International Symposium on Intelligent Signal Processing and Communication Systems, Taipei, Taiwan, Dec. 3\u20136, O28-6, 2019<\/li>\n\n\n\n
        16. M. Shiiba, M. Muneyasu and S. Yoshida : New Data Embedding and Detecting Method for Printed Image, Proc. 2019 IEEE 8th Global Conference on Consumer Electronics, Osaka, Japan, Oct.15\u201318, pp.223-224, 2019<\/li>\n\n\n\n
        17. H. Takeda, S. Yoshida and M. Muneyasu : Tag-based Video Retrieval with Social Tag Relevance Learning, Proc. 2019 IEEE 8th Global Conference on Consumer Electronics, Osaka, Japan, Oct.15\u201318, pp.893-894, 2019<\/li>\n\n\n\n
        18. S. Yoshida and M. Muneyasu : A Graph-based Video Visual Reranking Method via Heterogenous Graph Analysis, Proc. 2019 International Workshop on Smart Info-Media Systems in Asia, Tokyo, Japan, Sept.4\u20136, pp.161-166, 2019<\/li>\n\n\n\n
        19. M. Shiiba, T. Nishikawa, M. Muneyasu and S. Yoshida : Improvement of Data Embedding Method for Printed Image with High Detection Rate, Proc. 2019 International Workshop on Smart Info-Media Systems in Asia, Tokyo, Japan, Sept.4\u20136, pp.167-171, 2019<\/li>\n\n\n\n
        20. M. Muneyasu : Recent Advances of Information Retrieval by Data Embedding Technique to Printed Images Using Mobile Devices (Keynote Speech), Proc. 2019 International Workshop on Smart Info-Media Systems in Asia, Tokyo, Japan, Sept.4\u20136, 2019<\/li>\n\n\n\n
        21. M. Amami, M. Muneyasu, and S. Yoshida : Data Extraction for Data-embedded Printed Image Arranged at Arbitrary Positions, Proc. 2018 International Workshop on Smart Info-Media Systems in Asia, Kanagawa, Japan, Dec.13\u201314, pp.92-97, 2018<\/li>\n\n\n\n
        22. S. Yoshida, and M. Muneyasu : Video Search Reranking on Multi-Layer Graphs Based on Combination of Video Features Using Subspace Analysis, Proc. 2018 International Workshop on Smart Info-Media Systems in Asia, Kanagawa, Japan, Dec.13\u201314, pp.53-58, 2018<\/li>\n\n\n\n
        23. S. Oohara, M. Muneyasu, S. Yoshida, and M. Nakashizuka : Image Regularization Using Total Variation and Morphological Gradient Priors with Optimization of Structuring Element, Proc. 2018 International Symposium on Intelligent Signal Processing and Communication Systems, Ishigaki, Japan, Nov.27\u201330, pp.498-503, 2018<\/li>\n\n\n\n
        24. T. Fujii, S. Yoshida, and M. Muneyasu : Video Retrieval by Reranking and Relevance Feedback with Tag-Based Similarity, Proc. 2018 IEEE 7th Global Conference on Consumer Electronics, Nara, Japan, Sept.6\u20138, pp.659-660, 2018 (IEEE GCCE 2018 Excellent Poster Award 3rd Prize)<\/mark><\/li>\n\n\n\n
        25. H. Oka, S. Oohara, M. Muneyasu, S. Yoshida, and M. Nakashizuka : Image Regularization with Morphological Gradients Priors Using Optimization of Multiple Structuring Element, Proc. 2018 International Symposium on Multimedia and Communication Technology, Tottori, Japan, Aug.29\u201331, pp.32-35, 2018<\/li>\n\n\n\n
        26. T. Nishigaito, M. Muneyasu, K. Matsushima, S. Yoshida, and A. Taguchi : A New Method of Lossless Cording for Binary Holographic Interference Fringes, Proc. 2017 International Workshop on Smart Info-Media Systems in Asia, Dazaifu, Fukuoka, Sept.6\u20138, pp.1-4, 2017<\/li>\n\n\n\n
        27. S. Oohara, Y. Ikeshita, M. Muneyasu, S. Yoshida, and M. Nakashizuka : Image Regularization with Morphological Gradient Priors Using Optimization of Structuring Element, Proc. 2017 International Workshop on Smart Info-Media Systems in Asia, Dazaifu, Fukuoka, Sept.6\u20138, pp.61-65, 2017<\/li>\n\n\n\n
        28. T. Fujii, S. Yoshida, and M. Muneyasu : Feedback Assisted Multi-modality Reranking for Web Video Search, Proc. 2017 International Workshop on Smart Info-Media Systems in Asia, Dazaifu, Fukuoka, Sept.6\u20138, pp.74-78, 2017<\/li>\n\n\n\n
        29. T. Nasu, K. Kawachi, M. Muneyasu, K. Chamnongthai, A. Asano, K. Uchida, Y. Ishioka, N. Yoshinari, and A. Taguchi : Detection of Calcification Region in Dental Panoramic Radiographs Using Snakes, Proc. 2017 International Workshop on Smart Info-Media Systems in Asia, Dazaifu, Fukuoka, Sept.6\u20138, pp.110-113, 2017<\/li>\n\n\n\n
        30. M. Liji, M. Muneyasu, K. Matsushima S. Yoshida, and A. Taguchi : Lossy Coding of Wave-field Data Using Singular Value Decomposition, Proc. 2017 International Workshop on Smart Info-Media Systems in Asia, Dazaifu, Fukuoka, Sept.6\u20138, pp.211-215, 2017<\/li>\n\n\n\n
        31. Y. Ikeshita, M. Muneyasu, M. Nakashizuka, and S. Yoshida : Image Regularization with Morphological Gradients Priors Considering Optimization of SE, Proc. 2017 Taiwan and Japan Conference on Circuits and Systems, Okayama, Japan, Aug. 21-23, pp.4, 2017<\/li>\n\n\n\n
        32. S. Abe, M. Muneyasu, and S. Yoshida : A Design Technique of Impulse Detector Using Neural Network, Proc. 2017 Taiwan and Japan Conference on Circuits and Systems, Okayama, Japan, Aug. 21-23, pp. 19, 2017<\/li>\n\n\n\n
        33. S. Yoshida, T. Ogawa, M. Haseyama and M. Muneyasu : Heterogeneous Graph-Based Topic Learning for Web Video Search Reranking, Proc. 2016 International Workshop on Smart Info-Media Systems in Asia, Ayutthaya, Thailand, Sept.14\u201317, pp.81-85\uff0c2016<\/li>\n\n\n\n
        34. T. Shintani, M. Muneyasu and S. Yoshida : Improved Object Detection Method Using PTZ Camera and Kinect, Proc. 2016 International Workshop on Smart Info-Media Systems in Asia, Ayutthaya, Thailand, Sept.14\u201317, pp.75-80\uff0c2016<\/li>\n\n\n\n
        35. N. Jinda, M. Shiiba and M. Muneyasu : Implementation of Data Extraction for Data Embedding to Printed Images in Tablet PC and Its Evaluation, Proc. 2016 International Workshop on Smart Info-Media Systems in Asia, Ayutthaya, Thailand, Sept.14\u201317, pp.69-74\uff0c2016<\/li>\n\n\n\n
        36. K. Fujii and M. Muneyasu : A Method Stably Working Feedback Type Active Noise Control System for Preventive Panel of Sound Leakage, Proc. the 45th International Congress and Exposition on Noise Control Engineering, Hamburg, Germany, Aug.21-24, pp.426-437, 2016<\/li>\n\n\n\n
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        38. S. Yoshida, T. Ogawa, and M. Haseyama : Heterogeneous Graph-based Video Search Reranking using Web Knowledge via Social Media Network,\u201d Proc. ACM International Conference on Multimedia (ACM MM), pp. 871-874, Brisbane, Australia, October, 2015 (Acceptance rate: 22%, Core Conference Ranking A*)<\/li>\n<\/ol>\n\n\n\n
          <\/div>\n\n\n\n

          <\/p>\n\n\n\n

          \u56fd\u5185\u4f1a\u8b70<\/h2>\n\n\n\n

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