{"id":872,"date":"2019-04-01T17:58:43","date_gmt":"2019-04-01T08:58:43","guid":{"rendered":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/?page_id=872"},"modified":"2020-04-02T12:27:28","modified_gmt":"2020-04-02T03:27:28","slug":"2018%e5%b9%b4%e5%ba%a6%e8%ab%96%e6%96%87%e3%83%aa%e3%82%b9%e3%83%88","status":"publish","type":"page","link":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/?page_id=872","title":{"rendered":"2018\u5e74\u5ea6\u8ad6\u6587\u30ea\u30b9\u30c8"},"content":{"rendered":"\n<h3>\u8ad6\u6587<\/h3>\n<ul>\n<li>Yu Enokibori and Kenji Mase. &#8220;Data Augmentation to Build High Performance DNN for In-bed Posture Classification&#8221;, Journal of Information Processing, Vol. 26, pp.718-727, 2018.<\/li>\n<li> \u5c0f\u91ce\u702c\u826f\u4f51, \u698e\u5800\u512a, \u9593\u702c\u5065\u4e8c. \u8925\u7621\u770b\u8b77\u30b1\u30a2\u652f\u63f4\u306b\u5411\u3051\u305f\u4f53\u8868\u5727\u3092\u8a08\u6e2c\u53ef\u80fd\u306a\u8863\u985e\u578b\u5727\u529b\u30bb\u30f3\u30b5\u306e\u7814\u7a76. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.59(10), pp. 1827-1836, 2018. <\/li>\n<\/ul>\n<h3>\u56fd\u969b\u4f1a\u8b70<\/h3>\n<ul>\n<li>Ryosuke Onose, Yu Enokibori, Yuko Harasawa, Kenji Mase, \u201cTextile Sensor based Visualization to Enhance Skills to Understand Body Pressure Distribution for Pressure Ulcer Prevention\u201d, The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018) Poster, Singapore, 2018.10.8-10.12<\/li>\n<li>Ryosuke Onose, \u201cUser-Friendly Design of Caregiving Support System\u201d, The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2018) Doctoral Colloquium, Singapore, Poster, 2018.10.8-10.12<\/li>\n<\/ul>\n<h3>\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u30fb\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7<\/h3>\n<ul>\n<li>\u6e21\u8fba\u535a\u6587\uff0c\u698e\u5800\u512a\uff0c\u7c73\u6fa4\u670b\u5b50\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u767d\u6756\u5148\u7aef\u523a\u6fc0\u63d0\u793a\u306b\u3088\u308b\u4eee\u60f3\u8a98\u5c0e\u8def\u30c7\u30b6\u30a4\u30f3\u306e\u691c\u8a0e&#8221;\uff0cDICOMO2018\uff0c\u82a6\u539f\u6e29\u6cc9\u6e05\u98a8\u8358\uff0c\u798f\u4e95\uff0c2018.7.4-6.<\/li>\n<li>\u5c0f\u91ce\u702c \u826f\u4f51\uff0c\u6797 \u5343\u5c0b\uff0c\u698e\u5800 \u512a\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u30b9\u30de\u30fc\u30c8\u8eca\u6905\u5b50\u3092\u7528\u3044\u305f\u8001\u4eba\u30db\u30fc\u30e0\u306b\u304a\u3051\u308b\u7d99\u6642\u8a08\u6e2c\u306e\u8a55\u4fa1&#8221;\uff0cDICOMO2018\uff0c\u82a6\u539f\u6e29\u6cc9\u6e05\u98a8\u8358\uff0c\u798f\u4e95\uff0c2018.7.4-6.<\/li>\n<li>Jinseok Moon, Junya Morita, Yu Enokibori, Takatsugu Hirayama, Albert Ali Salah, Kenji Mase, Yoshiyuki Hatakeyama and Hirotaka Kaji, &#8220;Predicting Signs of Drowsiness from Driver&#8217;s Blinking and Driving Behavior&#8221;\uff0cDSP in vehicles 2018\uff0cNagoya University\uff0cNagoya\uff0c2018.10.7-9.<\/li>\n<li>\u6e21\u8fba\u535a\u6587\uff0c\u698e\u5800\u512a\uff0c\u7c73\u6fa4\u670b\u5b50\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u767d\u6756\u5148\u7aef\u523a\u6fc0\u63d0\u793a\u306b\u3088\u308b\u4eee\u60f3\u8a98\u5c0e\u8def\u30c7\u30b6\u30a4\u30f3\u306e\u691c\u8a0e&#8221;\uff0c\u60c5\u5831\u5b66\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7(WiNF)2018\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\uff0c\u611b\u77e5\uff0c2018.11.10.<\/li>\n<\/ul>\n<h3>\u7814\u7a76\u4f1a<\/h3>\n<ul>\n<li>\u5ca1\u7530\u76f4\u4eba\uff0c\u6e25\u7f8e\u88d5\u8cb4\uff0c\u6a2a\u77e2\u771f\u60a0\uff0c\u5c71\u7530\u548c\u7bc4\uff0c\u6c6a\u96ea\u30c6\u30a4\u0003\uff0c\u4e0a\u51fa\u5bdb\u5b50\uff0c\u68ee\u7530\u7d14\u54c9\uff0c\u698e\u5800\u512a\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u5fc3\u8eab\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u8a13\u7df4\u306b\u3088\u308b\u8eab\u4f53\u80fd\u529b\u6539\u5584\u52b9\u679c\u306e\u691c\u8a0e&#8221;\uff0c\u30e1\u30c7\u30a3\u30a2\u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u30fb\u30d0\u30fc\u30c1\u30e3\u30eb\u74b0\u5883\u57fa\u790e\u7814\u7a76\u4f1a(MVE)\uff0c\u65e5\u672c\uff0c\u6771\u4eac\u5927\u5b66\uff0c2018.6.14-15.(COI)<\/li>\n<li>\u6a9c\u4f5c\u5b5f\u5fd7\uff0c\u5e73\u5c71\u9ad8\u55e3\uff0c\u698e\u5800\u512a\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u65e5\u5e38\u7269\u4f53\u753b\u50cf\u3092\u7528\u3044\u305f\u5909\u5316\u691c\u51fa\u8ab2\u984c\u306b\u304a\u3051\u308b\u96e3\u6613\u5ea6\u8abf\u7bc0\u624b\u6cd5\u306e\u691c\u8a0e&#8221;\uff0c\u30e1\u30c7\u30a3\u30a2\u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u30fb\u30d0\u30fc\u30c1\u30e3\u30eb\u74b0\u5883\u57fa\u790e\u7814\u7a76\u4f1a(MVE)\uff0c\u65e5\u672c\uff0c\u6771\u4eac\u5927\u5b66\uff0c2018.6.14-15.(COI)<\/li>\n<li>\u9593\u702c\u5065\u4e8c, &#8220;e-\u30b3\u30fc\u30c1\u30f3\u30b0\u7814\u7a76\u306b\u304a\u3051\u308b\u30e1\u30c7\u30a3\u30a2\u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u8ab2\u984c&#8221;\uff0c\u30e1\u30c7\u30a3\u30a2\u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u30fb\u30d0\u30fc\u30c1\u30e3\u30eb\u74b0\u5883\u57fa\u790e\u7814\u7a76\u4f1a(MVE)\uff0cMVE2018-20, \u5927\u962a\u5de5\u5927\uff0c2018.9.6-7\u3000(COI, SCOPE, \u79d1\u781420280074\u57fa\u76e4B)<\/li>\n<li>\u6a9c\u4f5c\u5b5f\u5fd7\uff0c\u698e\u5800\u512a\uff0c\u9593\u702c\u5065\u4e8c\uff0e\u65e5\u5e38\u7269\u4f53\u753b\u50cf\u306b\u5bfe\u3059\u308b\u7a7a\u9593\u7684\u6ce8\u610f\u306b\u7740\u76ee\u3057\u305f\u96e3\u6613\u5ea6\u8abf\u7bc0\u53ef\u80fd\u306a\u8996\u899a\u7684\u8a8d\u77e5\u8ab2\u984c\u306e\u691c\u8a0e\uff0c\u30d2\u30e5\u30fc\u30de\u30f3\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u57fa\u790e\u7814\u7a76\u4f1a\uff08HCS\uff09\uff0c\u5317\u6d77\u9053\u672d\u5e4c\uff0c\u5317\u661f\u5b66\u5712\u5927\u5b66\uff0c2019.3.7-3.8 (COI)<\/li>\n<li>\u5ca1\u7530\u76f4\u4eba\uff0c\u6e25\u7f8e\u88d5\u8cb4\uff0c\u6a2a\u77e2\u771f\u60a0\uff0c\u5c71\u7530\u548c\u7bc4\uff0c\u68ee\u7530\u7d14\u54c9\uff0c\u4e0a\u51fa\u5bdb\u5b50\uff0c\u5409\u5ddd\u5927\u5f18\uff0c\u53e4\u6a4b\u6b66\uff0c\u698e\u5800\u512a\uff0c\u9593\u702c\u5065\u4e8c\uff0e\u6b69\u884c\u652f\u63f4\u30ed\u30dc\u30c3\u30c8\u3092\u7528\u3044\u305f\u9ad8\u9f62\u8005\u306e\u5fc3\u8eab\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u52b9\u679c\u306e\u691c\u8a0e\uff0c\u30e1\u30c7\u30a3\u30a2\u30a8\u30af\u30b9\u30da\u30ea\u30a8\u30f3\u30b9\u30fb\u30d0\u30fc\u30c1\u30e3\u30eb\u74b0\u5883\u57fa\u790e\u7814\u7a76\u4f1a\uff08MVE), \u9e7f\u5150\u5cf6\u770c\u9e7f\u5150\u5cf6\u5e02\uff0c\u9e7f\u5150\u5cf6\u5927\u5b66\uff0c2019.3.14-15 (COI)<\/li>\n<\/ul>\n<h3>\u5168\u56fd\u5927\u4f1a<\/h3>\n<ul>\n<li>\u6e25\u7f8e\u88d5\u8cb4,\u6a2a\u77e2\u771f\u60a0,\u5c71\u7530\u548c\u7bc4,\u5ca1\u7530\u76f4\u4eba,\u6c6a\u96ea&#23159;,\u68ee\u7530\u7d14\u54c9,\u4e0a\u51fa\u5bdb\u5b50,\u698e\u5800\u512a,\u9593\u702c\u5065\u4e8c, &#8220;\u5fc3\u8eab\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u30c8\u30ec\u30fc\u30cb\u30f3\u30b0\u304c\u9ad8\u9f62\u8005\u306e\u8a8d\u77e5\u80fd\u529b\u306b\u4e0e\u3048\u308b\u5f71\u97ff\u306e\u691c\u8a3c&#8221;, \u65e5\u672c\u8a8d\u77e5\u79d1\u5b66\u4f1a\u7b2c35\u56de\u5927\u4f1a, \u7acb\u547d\u9928\u5927\u5b66\u5927\u962a\u3044\u3070\u3089\u304d\u30ad\u30e3\u30f3\u30d1\u30b9, 2018.8.30 <\/li>\n<\/ul>\n<h3>\u652f\u90e8\u5927\u4f1a<\/h3>\n<ul>\n<li>\u6a4b\u53e3\u822a\uff0c\u68ee\u7530\u7d14\u54c9\uff0c\u5e73\u5c71\u9ad8\u55e3\uff0c\u9593\u702c\u5065\u4e8c\uff0c&#8221;\u751f\u4f53\u4fe1\u53f7\u3092\u7528\u3044\u305f\u30b9\u30c8\u30ec\u30b9\u5236\u5fa1\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u306e\u691c\u8a0e&#8221;\uff0c\u5e73\u621029\u5e74\u5ea6 \u96fb\u6c17\u30fb\u96fb\u5b50\u30fb\u60c5\u5831\u95a2\u4fc2\u5b66\u4f1a\u000b\u6771\u6d77\u652f\u90e8\u9023\u5408\u5927\u4f1a\uff0c\u540d\u53e4\u5c4b\u5927\u5b66\u30012017.9.7-8<\/li>\n<\/ul>\n<h3>\u7d00\u8981<\/h3>\n<h3>\u89e3\u8aac\u8a18\u4e8b\u3001\u30ec\u30d3\u30e5\u30fc\u3001\u5831\u544a\u66f8<\/h3>\n<h3>\u5c55\u793a\u4f1a<\/h3>\n<h3>\u62db\u5f85\u8b1b\u6f14<\/h3>\n<ul>\n<li>Kenji Mase, &#8220;Augmenting Visual Cognitive Interactions: from Wearable First-person View to Ubiquitous Third-person Multi-views&#8221;, 4-4 Information Photonics, 79th JSAP-OSA Joint Symposium, Nagoya, 2018.9.18-21 (invited talk) (COI, SCOPE)<\/li>\n<li>\u9593\u702c\u5065\u4e8c\u3001\u5171\u751f\u30a4\u30f3\u30bf\u30e9\u30af\u30b7\u30e7\u30f3\u7814\u7a76\u304c\u5c0e\u304f\u4eba\u9593\u3068AI\u306e\u65b0\u3057\u3044\u793e\u4f1a\u3001\u62db\u5f85\u8b1b\u6f14\u3001\u30ed\u30dc\u30c3\u30c8\u30b7\u30f3\u30dd\u30b8\u30a6\u30e02019\u540d\u53e4\u5c4b\u3001\u5439\u4e0a\u30db\u30fc\u30eb\u3001\u540d\u53e4\u5c4b\u5e02\u30012019.2.6\uff08COI,SCOPE,CREST)<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>\u8ad6\u6587 Yu Enokibori and Kenji Mase. &#8220;Data Augmentation to Build High Performance DNN for In-bed Posture Clas [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"parent":26,"menu_order":-2018,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/pages\/872"}],"collection":[{"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=872"}],"version-history":[{"count":1,"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/pages\/872\/revisions"}],"predecessor-version":[{"id":873,"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/pages\/872\/revisions\/873"}],"up":[{"embeddable":true,"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=\/wp\/v2\/pages\/26"}],"wp:attachment":[{"href":"https:\/\/www.cmc.is.i.nagoya-u.ac.jp\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=872"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}