Course Prefix:CSECourse #: 455Keywords:nullshowing 1 to 1 of ~1
CSE 455LEC Introduction to Pattern Recognition
Lecture
Foundations of pattern recognition algorithms and machines, including statistical and structural methods. Data structures for pattern representation, feature discovery and selection, classification vs. description, parametric and non-parametric classification, supervised and unsupervised learning, use of contextual evidence, clustering, recognition with strings, and small, sample-size problems.
Credits:
3 Grading: Graded (GRD) Typically Offered:
Fall, Spring Prerequisites: (CSE 250 or EAS 230 or EAS 240 or CSE 115 or EAS 999TRCP) and EAS 305 or STA 301 or MTH 411; Approved CS, CE, Bioinformatics/CS Majors Only. Students must complete a mandatory advisement session with their faculty advisor.