CPE 407:Biometrics and machine learning

CATALOG DATA

Fundamentals of Biometric Science and Technology including probability theory, statistics, pattern recognition, and linear regression. Applications to Security, Robotics, Autonomous Navigation, Bioinformatics and Healthcare

COREQUISITES AND PREREQUISITES

Pre-req: Math 283 or CpE 260 with a grade of C or better. Advanced Standing required.

CREDITS-CONTACT HRS:

3 Credit hrs, 2.5 Contact hrs/week

TEXTBOOKS

  1. Introductory engineering statistics by S.S. Wilks, TA 340 G8 1982 (suggested)
  2. Introduction to Pattern Recognition by Menahem Friedman, Abraham Kandel, TK 7882 P3 F75, 1999 (suggested)
  3. Pattern Recognition by Bow, 2008 (recommended)
  4. Second Generation Biometrics: the Ethical, Legal and Social Context,Mordini, Emilio, Springer 2012

COORDINATOR:

Dr. ShahramLatifi

INSTRUCTORS:

S. Latifi

TOPICS

  • Elements of Probability
  • Important Discrete Distributions
  • The Normal Distribution
  • Basic Concepts in Pattern Recognition
  • Classifiers
  • Decision Functions
  • Classification by Distance Functions and Clustering
  • Types of Biometrics
  • Finger print recognition
  • Facial recognition
  • Voice recognition
  • Iris scanning
  • Retina scanning
  • Signature recognition and keystroke dynamics
  • Vein pattern
  • DNA
  • Ear
  • Gait
  • Multimodal Biometrics

COURSE OUTCOMES (ABET course outcomes) [UULO course outcomes]:

Upon completion of this course, students should be able to:

  1. Understand the concepts of Probability, Continuous and Discrete Distribution (a,b) [1,2]
  2. Understand Fundamentals of Statistics, Hypotheses, Normal Distribution (a,b) [1,2]
  3. Become familiar with fundamentals of Pattern Recognition (a,b,e) [1,2]
  4. Understand basic classification algorithms (c,e)[1,2]
  5. Understand different types of Biometrics (a,d,e,i,j,k)[1,2,4,5]
  6. Become familiar with Multimodal Biometrics (j,k)[1,2,4,5]

STUDENT OUTCOMES

(a) an ability to apply knowledge of mathematics, science, and engineering

(b) an ability to design and conduct experiments, as well as to analyze and interpret data

(c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability

(d) an ability to function on multidisciplinary teams

(e) an ability to identify, formulate, and solve engineering problems

(f) an understanding of professional and ethical responsibility

(g) an ability to communicate effectively

(h) the broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context

(i) a recognition of the need for, and an ability to engage in life-long learning

(j) a knowledge of contemporary issues

(k) an ability to use the techniques, skills, and modern engineering tools necessary for engineering practice.

UULO COURSE OUTCOMES

1. Intellectual Breadth and Lifelong Learning

2. Inquiry and Critical Thinking

3. Communication

4. Global/Multicultural Knowledge and Awareness

5. Citizenship and Ethics

COMPUTER USAG:

MATLAB

CLASS SCHEDULE:

Lecture 3 hours per week

GRADING:

Homework (15%), Test 1 (15%), Test 2 (15%), Term Paper (35%), Final (20%)

COURSE SYLLABUS PREPARER AND DATE

S. LatifiFebruary 12, 2018