Home Page / News

Syllabus

Course Description

An introduction to pattern classification and structural pattern recognition. Topics include Bayesian decision theory, evaluation, clustering, feature selection, classification methods (including linear classifiers, nearest-neighbor rules, support vector machines, and neural networks), classifier combination, and recognizing structures (e.g. using HMMs and SCFGs). Students will present current research papers and complete programming projects such as optical character recognizers.

Pre-requisites: CSCI-331, CSCI-630, or permission of the instructor. Credit Hours: 3

Course Outcomes

Assessment method(s) for each learning outcome are shown in italics.

  • Students will understand Bayesian Decision Theory, the canonical classifier model, and how different classification methods define decision boundaries. Evaluation: Assignments, and projects.
  • Students will be able to apply performance evaluation methods for pattern recognition. Evaluation: Projects.
  • Students will be able to select appropriate techniques for addressing recognition problems. Evaluation: Assignments, and projects.
  • Students will be able to implement basic pattern recognition algorithms. Evaluation: Assignments and projects.
  • Students will be able to summarize current pattern recognition research verbally and in writing. Evaluation: Assignments and research paper presentations.

Instructor Contact

The instructor checks course email weekdays Mon-Fri until Fri at noon.  The instructor will not respond to questions about assignments/projects the day that they are due, and will respond to emails sent after noon on Fridays on the following Monday.

Office hours are held online this semester. The Zoom link for office hours can be found through the MyCourses shell for the course.

Dr. Richard Zanibbi    E-mail: rxzvcs@rit.edu    Webhttps://www.cs.rit.edu/~rlaz/
Office: GOL-3551  (during COVID, time in my office is irregular)

Grading Scheme

Quizzes (10) 15

15% of Final Grade
There will be weekly online quizzes due before class on Thursdays. Students can retake them multiple times up to the deadline.

Research Papers (3)

15% of Final Grade
Students will present and/or discuss 3 papers during the semester online and/or in-class.

Assignments (4)

40% of Final Grade
Students will complete four individual assignments.

Projects (3)

30% of Final Grade
Students will complete 3 projects in teams. The final project serves as the examination for the course.

Course Policies

Course Policies on Grading

For full points, deliverables in the course, including question answers, code, presentations, and write-ups must be:
(1) correct and complete, (2) justified where asked (e.g., 'explaining' an answer), (3) clearly written, and (4) provided in the requested format(s).

Late Policy: Late submissions will be accepted up to 48 hours after the deadline with a 20% penalty.

Grade Adjustments: Requests for grade adjustments muse be received within one week of work being handed back.

Other Courses Policies

Submissions: All home work, both written and code, must be handed in via MyCourses. Note that for all programming homeworks/labs, they must be (easily) executable on the CS lab Linux machines. More details on allowed and available libraries etc will be given with each assignment (what is allowed for some may not be allowed for others).

Homework and Projects:  Homework will be completed individually, while projects are done in groups. Students must create all submitted homework on their own: it is not acceptable for a student to prepare an answer or answer set and share this with other students. Students may discuss homework and project work with other students, provided that students/groups produce their submitted work on their own.

Exam.  The exam will be a presentation of student's final projects.

Required Materials: All required materials for the course, including readings will be provided through MyCourses.

Attendance

Delivery of the course is synchronous, blended (i.e., in-person + online each lecture), and full-flex. Students who wish to attend in-person should attend only on their scheduled day each week (Tuesday / Thursday). Students who would prefer to attend online may do so using the Zoom links provided on MyCourses. The course is full-flex, meaning that with permission of the instructor, you may switch between in-person and online lecture participation. Whether in-person or online, attendance is required for this course, and attendance and seating charts will be recorded each lecture.

At some point in the semester lectures may move entirely online. This will happen if: 1) RIT stops in-person lectures due to COVID, or 2) a large majority of the class agrees to move lectures online.

Note that RIT’s official policy on attendance states that:

"Absences, for whatever reason, do not relieve students of their responsibility for fulfilling normal requirements in any course. In particular, it is the student’s responsibility to make individual arrangements in advance of missing class due to personal obligations such as religious holidays, job interviews, athletic contests, etc., in order that he or she may meet his or her obligations without penalty for missing class."  (RIT Governance Policy D4.0, Section I.B)

Therefore, if a student needs to miss class, there are mutual responsibilities for students and faculty. It is the student’s responsibility to notify the faculty member in advance of the planned absence. With advance notice of the planned absence, it is the faculty member’s responsibility to ensure that the student can fulfill all class assignments and expectations without penalty or bias.

RIT Department of Computer Science Policies

Academic Integrity

You should only submit work that is completely your own. Failure to do so counts as academic dishonesty and so does being the source of such work. Submitting work that is in large part not completely your own work is a flagrant violation of basic ethical behavior and will be punished according to department policy. 

Rescheduling Exams

Exams can not be made up except for real emergencies in which case proper documentation (like a doctor's note) will be required. If at all possible, you should contact me prior to the exam. Oversleeping, cars that don't start etc. do not constitute a valid excuse. RIT's Academic Senate revised the Final Examination Policies on March 28, 2013. Please refer to the policies for related questions.

Course Withdrawl

During the add/drop period, you may drop this course and it will disappear from your transcript. After that time, you can only withdraw from the course; the course will appear on your transcript with a grade of W. See the institute's calendar regarding the add/drop period and latest withdrawal date.

Disability Services

RIT is committed to providing reasonable accommodations to students with disabilities. If you would like to request accommodations such as special seating or testing modifications due to a disability, please contact the Disability Services Office. It is located in the Student Alumni Union, Room 1150; the web site is www.rit.edu/dso. After you receive accommodation approval, it is imperative that you see me during office hours so that we can work out whatever arrangement is necessary. 

Department of Computer Science
Rochester Institute of Technology