Image processing algorithms in biometrics and bioinformatics Field of study: Computer Science
Programme code: W4-S2INA19.2021

Module name: Image processing algorithms in biometrics and bioinformatics
Module code: W4-INA-S2-20-F-APOBi
Programme code: W4-S2INA19.2021
Semester:
  • summer semester 2022/2023
  • winter semester 2022/2023
  • summer semester 2021/2022
Language of instruction: English
Form of verification: course work
ECTS credits: 4
Description:
The course aims at introducing the students to image processing algorithms used in biometrics and bioinformatics.
Prerequisites:
(no information given)
Key reading:
1. Sandipan Dey, "Hands-On Image Processing with Python: Expert techniques for advanced image analysis and effective interpretation of image data", Packt, 2018. 2. Anil K. Jain, et al., "Handbook of Biometrics", Springer, 2008. 3. Juan Caballero, "Hands-On Bioinformatics with Python", Packt, 2019.
Learning outcome of the module Codes of the learning outcomes of the programme to which the learning outcome of the module is related [level of competence: scale 1-5]
The student knows and can explain the operation of image processing methods in biometrics and bioinformatics [M_001]
 K_W02 [5/5]
The student can prepare a presentation on the subject. [M_002]
 K_U04 [5/5]
The student can analyse and solve the problems of image processing in biometrics and bioinformatics. [M_003]
 K_U09 [5/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Written test. [W_001]
The test comprises theoretical questions concerning the issues discussed in the lectures.
 M_001
Presentation on the assigned topic. [W_002]
The students prepare presentations related to the lectures.
 M_002
Oral test [W_003]
The students elaborate on a topic related to image processing in biometrics and bioinformatics.
 M_003
Form of teaching Student's own work Assessment of the learning outcomes
Type Description (including teaching methods) Number of hours Description Number of hours
lecture [Z_001]
The content of the lecture will be available in the multimedia form, presenting the issues related to the topic.
 15
The students self-study the issues presented in the lectures. The students prepare for the exam individually.
 30 Written test. [W_001] Presentation on the assigned topic. [W_002] Oral test [W_003]
laboratory classes [Z_002]
During the classes, the students prepare tools for the implementation of design applications and complete tasks specified by the teacher.
 30
The students implement a project at home or on computers at the Institute.
 45 Written test. [W_001] Presentation on the assigned topic. [W_002] Oral test [W_003]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)