{"id":31,"date":"2020-03-14T21:08:49","date_gmt":"2020-03-14T12:08:49","guid":{"rendered":"http:\/\/d7ae1c2e.ap.ngrok.io\/?page_id=31"},"modified":"2020-03-15T01:14:45","modified_gmt":"2020-03-14T16:14:45","slug":"%e3%83%a1%e3%83%b3%e3%83%90%e3%83%bc%e3%81%ae%e4%bb%a3%e8%a1%a8%e7%9a%84%e3%81%aa%e6%a5%ad%e7%b8%be","status":"publish","type":"page","link":"https:\/\/www.smartsociety-research.org\/?page_id=31","title":{"rendered":"\u30e1\u30f3\u30d0\u30fc\u306e\u4ee3\u8868\u7684\u306a\u696d\u7e3e"},"content":{"rendered":"\n
  1. T. Terada, M. Toyoura<\/strong>, T. Sato, X. Mao<\/strong>, “Functional Fabric Pattern -Examining the Case of Pres-sure Detection and Localization,” IEEE Trans. on Industrial Electronics, Vol.66, No.10, pp.8224-8234, 2019.10.<\/li>
  2. M. Okawa, T. Saito, N. Sawada, H. Nishizaki<\/strong>, “Audio Classification of Bit-Representation Waveform,” Proc. of INTERSPEECH2019, pp.2553-2557, 2019.9<\/li>
  3. \u897f\u548c\u6a39\uff0c\u53e4\u5c4b\u8cb4\u5f66<\/strong>\uff0c\u5927\u6e15\u7adc\u592a\u90ce\uff0c\u201c\u6575\u5bfe\u7684\u751f\u6210\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f3\u6b21\u5143\u70b9\u7fa4\u5f62\u72b6\u7279\u5fb4\u91cf\u306e\u6559\u5e2b\u306a\u3057\u5b66\u7fd2\u201d\uff0c\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c\uff0cVol.60\uff0cNo.7\uff0cpp.1315-1324\uff0c2019.7<\/li>
  4. K. Makino<\/strong>, Y. Ogawa,T. Kanagawa, M. Matsuzaka, S. Yamamoto, K. Yamada, S. Shimada. T. Kawamura, H. Terada, “Presence of a family history and excessive pressure on the first toe pad during walking in female subjects with pincer nails,\u201d Journal of Dermatology, 46, pp.631\u2013633, 2019.<\/li>
  5. H. Nishizaki<\/strong>, K. Makino<\/strong>, \u201cSignal Classification with Deep Learning,\u201d Proc. of the 2019 IEEE International Conference on Sensors and Nanotechnology, pp.81-84, 2019.7<\/li>
  6. K. Shimura, J. Li and F. Fukumoto<\/strong>, “Text Categorization by Learning Predominant Sense of Words as Auxiliary Task, ” Proc. of ACL (1), pp.1109-1119, 2019<\/li>
  7. K. Makino<\/strong>, Y. Kitano, H. Nishizaki<\/strong>, “Classification of Swing Motion of Tennis Using a Recurrent-based Neural Network,” Proc. of IEEE HSI 2019, pp.1-4, 2019.6<\/li>
  8. A. S. A. Sukor, A. Zakaria, N. A. Rahim, L. M. Kamarudin, R. Setchi, H. Nishizaki<\/strong>, “A hybrid approach of knowledge-driven and data-driven reasoning for activity recognition in smart homes,” Journal of Intelligent & Fuzzy Systems, vol. 36, no. 5, pp. 4177- 4188, 2019.5<\/li>
  9. C.S. Leow, H. Nishizaki<\/strong>, \u201cA Task Manual Creation Support System Using Automatic Speech Recognition,\u201dProc. of GCCE2018, pp.259-262, 2018.10<\/li>
  10. \u897f\u5d0e\u535a\u5149<\/strong>\uff0c\u30ec\u30aa \u30c1\u30fc\u30b7\u30e3\u30f3\uff0c\u7267\u91ce\u6d69\u4e8c<\/strong>\uff0c”\u5c0f\u578b\u30b3\u30f3\u30d4\u30e5\u30fc\u30bf\u306b\u304a\u3051\u308b\u6df1\u5c64\u5b66\u7fd2\u30a2\u30d7\u30ea\u30b1\u30fc\u30b7\u30e7\u30f3\u306e\u52d5\u4f5c\u691c\u8a3c”\uff0c\u96fb\u6c17\u5b66\u4f1a\u8ad6\u6587\u8a8cC\uff0cVol.138\uff0cNo.9\uff0cpp.1108-1115, 2018.9<\/li>
  11. T. Furuya<\/strong>, R. Ohbuchi, \u201cLearning part-in-whole relation of 3D shapes for part-based 3D model retrieval,\u201d Computer Vision and Image Understanding, Vol.166, pp.102-114, 2018<\/li>
  12. I. Mochizuki, M. Toyoura<\/strong>, X. Mao<\/strong>, “Visual Saliency Prediction for Images with Leading Line Structure,” The Visual Computer, Vol.34, No.6-8, pp.1031-1041, 2018<\/li>
  13. Y. Tang, Z. Zhu, M.Toyoura<\/strong>, K. Go, K. Kashiwagi, I. Fujishiro, X. Mao<\/strong>, “Arriving Light Control for Color Vision Deficiency Compensation Using Optical See-Through Head-Mounted Display,” ACM SIGGRAPH VRCAI, pp.1-6, 2018<\/li>
  14. K. Hosokawa, T. Ishii, T. Shimizu,<\/strong> \u201cAn Ultrasonic Motor with 2 Mm in Rotor Diameter Using Transmission Line and a Spring Washer Driven by a Lagevin Transducer,\u201d Proc. of the 2018 IEEE International Ultrasonics Symposium (IUS)<\/li>
  15. K. Shimura, J. Li and F. Fukumoto<\/strong>, \u201cHFT-CNN: Learning Hierarchical Category Structure for Multi-label Short Text Categorization,\u201d Proc. of EMNLP 2018, pp.811-816, 2018<\/li>
  16. T. Furuya<\/strong>, R. Ohbuchi, \u201cData Augmentation via Photo-to-Sketch Translation for Sketch-based Image Retrieval,\u201d Proc. of  International Conference on Graphics and Image Processing (ICGIP) 2018<\/li>
  17. H. Nishizaki<\/strong>, “Data augmentation and feature extraction using variational autoencoder for acoustic modeling,” Proc.of APSIPA ASC 2017, pp.1222-1227, 2017.12<\/li>
  18. T.Furuya<\/strong>, R. Ohbuchi, “Deep semantic hashing of 3D geometric features for efficient 3D model retrieval,” Proc. Computer Graphics International Conference 2017, Article No.8, 2017<\/li>
  19. M.Toyoura<\/strong>, T.Tanaka, A. Sugiura, X. Mao<\/strong>, “Improving Eye Tracking Accuracy by Head Motion History,” IIEEJ Transactions on Image Electronics and Visual Computing, Vol.5, No.2, pp.92-98, 2017<\/li>
  20. S. Lu, X. Jin, A. Jaffer, F. Gao, X. Mao<\/strong>, “Solid Mathematical Marbling,” IEEE Computer Graphics and Applications, Vol.37, No.2, pp.90-98, 2017<\/li>
  21. T. Ishii, M. Mochizuki, T. Shimizu<\/strong>, \u201cAn ultrasonic motor using transmission line and a spring washer driven by a Langevin transducer,\u201d Proc.of Meetings on Acoustics, 32\/ 065003, pp.1-5, 2017<\/li>
  22. F. Fukumoto<\/strong>, Y. Suzuki, A. Wangpoonsarp and M. Ji, “Integrating Local and Global Data View for Bilingual Sense, Correspondences,\u201d IC3K 2017, Springer, pp. 224-241, 2017<\/li><\/ol>\n","protected":false},"excerpt":{"rendered":"

    T. Terada, M. Toyoura, T. …<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":5,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/pages\/31"}],"collection":[{"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=31"}],"version-history":[{"count":3,"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/pages\/31\/revisions"}],"predecessor-version":[{"id":65,"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/pages\/31\/revisions\/65"}],"up":[{"embeddable":true,"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=\/wp\/v2\/pages\/5"}],"wp:attachment":[{"href":"https:\/\/www.smartsociety-research.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=31"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}