{"ModuleCode":"EE6733","ModuleTitle":"Advanced Topics on Vision and Machine Learning","Department":"Electrical & Computer Engineering","ModuleDescription":"This course is designed to give graduate students a comprehensive understanding of topics at the confluence of computer vision, computer graphics, machine learning and image processing. This module will expose students to the most recent research and highlight the foundations and trends in these fields. We will discuss selected papers on most recent research problems, with topics covering lighting, geometry, image processing, medical image analysis, recognition and machine learning.","ModuleCredit":"4","Workload":"3-0-0-3-4","Prerequisite":"EE5907 / EE5907R Pattern Recognition AND EE5731R Advanced Visual Computing.","AcadYear":"2014/2015","History":[{"Semester":1,"Timetable":[{"ClassNo":"1","LessonType":"Lecture","WeekText":"Every Week","DayText":"Thursday","StartTime":"1800","EndTime":"2100","Venue":"E3-06-13"}],"IVLE":[{"Announcements":null,"Forums":[],"Workbins":[],"Webcasts":[],"Gradebooks":[],"Polls":[],"Multimedia":[],"LessonPlan":[],"ID":"3a67f484-a163-48b7-ba14-e18086affc7c","CourseLevel":"1","CourseCode":"EE6733","CourseName":"ADVANCED TOPICS ON VISION AND MACHINE LEARNING","CourseDepartment":"","CourseSemester":"Semester 1","CourseAcadYear":"2014/2015","CourseOpenDate":"/Date(1405612800000+0800)/","CourseOpenDate_js":"2014-07-18T00:00:00","CourseCloseDate":"/Date(1417881540000+0800)/","CourseCloseDate_js":"2014-12-06T23:59:00","CourseMC":"0","isActive":"N","Permission":"S","Creator":{"UserID":null,"Name":"Cheong Loong Fah","Email":null,"Title":null,"UserGuid":"d5e365ea-2b81-4257-ad69-b36c7512b9b7","AccountType":null},"hasGradebookItems":false,"hasTimetableItems":true,"hasGroupsItems":false,"hasClassGroupsForSignUp":false,"hasGuestRosterItems":true,"hasClassRosterItems":false,"hasWeblinkItems":false,"hasLecturerItems":true,"hasDescriptionItems":true,"hasReadingItems":true,"hasAnnouncementItems":false,"hasProjectGroupItems":false,"hasProjectGroupsForSignUp":false,"hasConsultationItems":false,"hasConsultationSlotsForSignUp":false,"hasLessonPlanItems":false,"Badge":0,"BadgeAnnouncement":0,"WebLinks":[],"Lecturers":[{"ID":"896c3d7f-a01f-4a95-aebb-017d8f9ef3f8","User":{"UserID":null,"Name":"Cheong Loong Fah","Email":null,"Title":null,"UserGuid":"d5e365ea-2b81-4257-ad69-b36c7512b9b7","AccountType":null},"Role":"Lecturer ","Order":1,"ConsultHrs":null},{"ID":"34dac4e5-7754-4439-9c97-a696d8bd3307","User":{"UserID":null,"Name":"Yan Shuicheng","Email":null,"Title":null,"UserGuid":"0bb8b035-0f10-4132-a0e9-c92b102f85c5","AccountType":null},"Role":"Lecturer ","Order":2,"ConsultHrs":null},{"ID":"b292b694-ba3e-4f58-976c-a261cb18ff6f","User":{"UserID":null,"Name":"Yeo Boon Thye Thomas","Email":null,"Title":null,"UserGuid":"152ff877-1473-4db2-aec1-914e76e3d6d8","AccountType":null},"Role":"Co-Lecturer ","Order":3,"ConsultHrs":null}],"Descriptions":[{"ID":"1e5f053b-8835-4692-be49-41f07234cfff","Title":"Learning Outcomes","Description":"This course is designed to give graduate students a comprehensive understanding of topics at the confluence of computer vision, computer graphics, machine learning and image processing. This module will expose students to the most recent research and highlight the foundations and trends in these fields. We will discuss selected papers on most recent research problems, with topics covering lighting, geometry, image processing, medical image analysis, recognition and machine learning.
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\n\t\t\t\tLecturers will select state-of-the-art papers and guide the seminar discussion. Each year, the selection of papers will be refreshed. \n\t\t\t\t \n\t\t\t\tStudents will present and discuss these papers in class seminars. Assessment will be evaluated based on presentation, report writing, and class participation. \n\t\t\t\t | \n\t\t
\n\t\t\t\t \n\t\t\t\tReport writing (30%): Each non-presenting student needs to submit a one page report before the presentation, for at least half of the 12 seminars. The student should read the paper, raise his/her questions and comments in that report, and discuss them in class. This report should be submitted 3 days before the presentation, so that the presenter can think about these issues and address them in the presentation. Each student will submit about 6 reports through a semester, and the quality of the questions raised and the depth of the critique will be taken into account in the assessment. \n\t\t\t\t | \n\t\t