{"id":3190,"date":"2017-12-18T14:50:04","date_gmt":"2017-12-18T19:50:04","guid":{"rendered":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/?p=3190"},"modified":"2026-02-18T11:28:55","modified_gmt":"2026-02-18T16:28:55","slug":"3190","status":"publish","type":"post","link":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/2017\/12\/18\/3190\/","title":{"rendered":"Congratulations Dr. Xiaoxiao Du, our lab’s latest Ph.D. graduate!"},"content":{"rendered":"

\"\"<\/p>\n

Congratulations to Dr. Xiaoxiao Du for graduating with her Ph.D. this past week! Her dissertation is titled \u201cMultiple Instance Choquet Integral for Multi-resolution Sensor Fusion.\u201d Her research focused on developing trained sensor and classifier fusion methods that can learn from ambiguously and imprecisely labeled training data. The goal of her work is to optimize fusion while minimizing the effort needed to precisely label data.<\/p>\n

Read about more her research:<\/p>\n

X. Du<\/strong>, \u201cMultiple Instance Choquet Integral For Multi-Resolution Sensor Fusion<\/a>,\u201d Ph.D. Thesis, Columbia, MO, 2017.<\/p>\n

X. Du<\/strong>, A. Seethepalli, H. Sun, A. Zare and J. T. Cobb, \u201cEnvironmentally-Adaptive Target Recognition for SAS Imagery <\/a>\u201d in Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, 2017.<\/p>\n

J. T. Cobb, X. Du<\/strong>, A. Zare, and M. Emigh, \u201cMultiple-instance Learning-based Sonar Image Classification <\/a>\u201d in Proc. SPIE 10182, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXII, 2017.<\/p>\n

X. Du<\/strong>, A. Zare, J. Keller, and D. Anderson, \u201cMultiple Instance Choquet Integral for Classifier Fusion<\/a>,\u201d in IEEE Congr. Evol. Computation (CEC)<\/em>, Vancouver, BC, 2016, pp. 1054-1061.<\/p>\n

X. Du<\/strong>, A. Zare, and J. T. Cobb, \u201cPossibilistic context identification for SAS imagery<\/a>,\u201d in Proc. SPIE 9454, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XX, 2015.<\/p>\n

X. Du<\/strong>, A. Zare, P. Gader, and D. Dranishnikov, \u201cSpatial and Spectral Unmixing Using the Beta Compositional Model<\/a>,\u201d IEEE J. Sel. Topics. Appl. Earth Observ.<\/em>, vol. 7, pp. 1994-2003, June, 2014.<\/p>\n

X. Du<\/strong>, \u201cAccounting for Spectral Variability in Hyperspectral Unmixing Using Beta Endmember Distribution<\/a>,\u201d Master Thesis, Columbia, MO, 2013.<\/p>\n

 <\/p>\n","protected":false},"excerpt":{"rendered":"

Congratulations to Dr. Xiaoxiao Du for graduating with her Ph.D. this past week! Her dissertation is titled \u201cMultiple Instance Choquet Integral for Multi-resolution Sensor Fusion.\u201d Her research focused on developing trained sensor and classifier fusion methods that can learn from ambiguously and imprecisely labeled training data. The goal of her work is to optimize fusion […]<\/p>\n","protected":false},"author":28,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"single-templates\/single-sidebar-none.php","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"featured_post":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[9],"tags":[],"class_list":["post-3190","post","type-post","status-publish","format-standard","hentry","category-news"],"acf":[],"_links":{"self":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/3190","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/users\/28"}],"replies":[{"embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/comments?post=3190"}],"version-history":[{"count":1,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/3190\/revisions"}],"predecessor-version":[{"id":14927,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/posts\/3190\/revisions\/14927"}],"wp:attachment":[{"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/media?parent=3190"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/categories?post=3190"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/faculty.eng.ufl.edu\/machine-learning\/wp-json\/wp\/v2\/tags?post=3190"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}