CSC 595 Seminar in Computer Science
Fall 2009

W   9:00 - 9:50 CIS Conf Room/Digital Arts Lab
[Instructor Home] [Syllabus] [Course Calendar]

Instructor:

Dr. Karl Ricanek, Jr.

This instructor is available by email at ricanekk@uncw.edu, by telephone (962-4261), and during office hours (CI 2006).   Office hours are posted on the instructors home page and located on the door to his office.  In addition, students can arrange to meet with the professor outside of normal office hours by contacting him via email or phone or schedule using Outlook. 

Learning Strategies

You are expected to take an active role in your learning in this course. This includes regular attendance, paying attention in class, and completing all course requirements. You are encouraged to study with your classmates outside of class.

Student Resources Required:

Course Information:

Prerequisites: None.

This course is designed to introduce students to current technology in Biometrics, which includes soft biometrics, pattern recognition, dimensionality reduction, computer vision, etc. The student will devise his/her own focus area in Biometrics by researching a topic area and selecting 3 or more seminal articles in the area. The student be responsible for preparing an oral presentation of the article with relevant examples/illustrations/demos.

Undergraduates taking this course may substitute this course for CSC 495, in satisfying the oral communication competency requirement for the B. S. degree in computer science.

Participation:

Regular class attendance is mandatory. Completion of assignments will entail detailed research on specified topics and oral dissemination via presentations.

Evaluation:
Students will conduct research (semi-exhaustive literature reviews) on emerging technologies related to Biometrics to gain the necessary background and insight to develop and deliver presentations on the subject matter.  Students will be graded on their attire, which is business, oral deliverance, organization, and content of presentation and depth of knowledge of the field/article.

Student research areas can be selected from those provided below, or one approved by the instructor.

  1. Biometric algorithms: face recognition, iris recognition, periocular recognition, gait recognition, retinal recognition, vienal recognition, hand recognition, fingerprint, ear recognition, forensic face or iris, or other such modalities.
  2. Soft biometric algorithms: gender, age, race classification, pose determination, face detection, or other such techniques.
  3. Biometric fusion: template fusion and score fusion.
  4. Policy issues in deploying biometrics in the workplace, consumer/household, or border control.

Each audience member will evaluate the presenter using an evaluation form.  The presenter's grade for the presentation will be the average of the total score from the form.

Final Grade Calculation:

All students will have an equal number of presentations. Each presentation will be worth 40 points max. 20 points will be assigned for participation and attendance. All points will be summed to form a final score that will be linearly mapped to the numeric score shown below. 

    Numeric Score     Letter Grade     Quality Points 
  ====================================================               
     90.0 - 100           A                4.00 
     80.0 - 89.5          B                3.00
     70.0 - 79.5          C                2.00
     60.0 - 69.5          D                1.00
     00.0 - 59.5          F                0.00

Special Needs:

If you have a disability and need reasonable accommodation in this course, you should inform the instructor of this fact in writing within the first week of class or as soon as possible. If you have not already done so, you must register with the Office of Disability Services in Westside Hall (extension 3746) and obtain a copy of your Accommodation Letter. You should then meet with your instructor to make mutually agreeable arrangements based on the recommendations of the Accommodation Letter.

Code of Academic Responsibility and Conduct:

Students are responsible for submitting their own work. Students who cooperate on oral or written examinations or work without authorization share the responsibility for violation of academic principles, and the students are subject to disciplinary action even when one of the students is not enrolled in the course where the violation occurred.