COURSE UNIT TITLE

Offered By

Medical Informatics

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR KÖKTEN ULAŞ BIRANT

Offered to

Medical Informatics

Course Objective

In this course, It is aimed to give basic information to students regarding learning algorithms, neural networks and pattern recognition, image processing and computational vision applications. Three different types of learning, supervised, unsupervised and reinforcement learning applications will be explained and discussed.

Learning Outcomes of the Course Unit

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Recomended or Required Reading

1) S. Haykin, Neural Networks: A Comprehensive Foundation 2nd edition, (Prentice Hall, 1999)
2) K. Mehrotra, C. Mohan, and S. Ranka, Elements of Artificial Neural Networks, MIT Press, 1997.
3) C. Looney, Pattern Recognition Using Neural Networks, Oxford University Press, 1997
4) C. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.
5) J. Hertz, A. Krogh, R.G. Palmer, Introduction to the Theory of Neural Computation (Addison-Wesley, 1991)

Planned Learning Activities and Teaching Methods

Assessment Methods

Successful / Unsuccessful

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homeworks, projects and exams

Language of Instruction

Turkish

Course Policies and Rules

Attendance is an essential requirement of this course and is the responsibility of the student. Students are expected to attend all lecture and recitation hours. Attendance must be at least 70% for the lectures.

Contact Details for the Lecturer(s)

Dokuz Eylül Üniversitesi, Faculty of Engineering, Department of Electrical and Electronics
e-mail: guleser.kalayci@deu.edu.tr
Tel: 0232 301 71 52

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Contribution of Learning Outcomes to Programme Outcomes