Artificial intelligence in computer graphics Field of study: Computer Science
Programme code: W4-S2INA19.2020

Module name: Artificial intelligence in computer graphics
Module code: W4-INA-S2-20-F-SIwGK
Programme code: W4-S2INA19.2020
Semester:
  • summer semester 2021/2022
  • winter semester 2021/2022
  • summer semester 2020/2021
Language of instruction: English
Form of verification: course work
ECTS credits: 4
Description:
The course aims at acquainting the students with issues related to the use of artificial intelligence methods in computer graphics.
Prerequisites:
(no information given)
Key reading:
1. Michalewicz Z., Fogle B. D.: How to Solve It: Modern Heuristics. Springer, 2004, 2. Plemenos D., Miaoulis G. (Eds.): Intelligent Computer Graphics. Springer, 2012, 3. Plemenos D., Miaoulis G.: Visual Complexity and Intelligent Computer Graphics Techniques Enhancements. Springer, 2009.
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 evolutionary algorithms, neural networks, and machine learning methods and understands optimisation and control issues. The student knows how to define a problem, find a solution, develop a mathematical model, and apply selected artificial intelligence algorithms. [M_001]
 K_W01 [1/5] K_W02 [1/5] K_W05 [1/5] K_U01 [1/5] K_U06 [1/5] K_U08 [1/5] K_K01 [1/5] K_K03 [1/5]
The student knows the rules of modelling 3D scenes, e.g. problems of physical environment simulation, motion planning, object detection, or collision avoidance. [M_002]
 K_W04 [1/5] K_W05 [1/5] K_U02 [1/5] K_U04 [1/5] K_K01 [1/5]
The students can work individually or in a team, understand the importance of intellectual honesty in their and other people's activity. They understand the need to improve their competencies continuously. The student thinks creatively, form opinions on fundamental issues, current state and development trends in IT, and understands non-technical issues of professional activity. [M_003]
 K_W03 [1/5] K_W04 [1/5] K_W05 [1/5] K_U01 [1/5] K_U02 [1/5] K_U03 [1/5] K_U04 [1/5] K_K01 [1/5] K_K02 [1/5] K_K03 [1/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Project [W_001]
The students implement of a semester project in learning outcomes adopted in the module.
 M_001 M_003
Project presentation [W_002]
The students present the project in front of the group, discussion of the assumptions and the adopted method of solving a specific problem, analysing and assessing the project goal's implementation.
 M_003
Test [W_003]
The test comprises open and closed-ended questions
 M_001 M_002
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 course is presented in a multimedia form.
 15
The students are required to self-study the lecture topics and recommended literature.
 30 Test [W_003]
laboratory classes [Z_002]
The students practice implementing the curriculum elements as assigned tasks on computer stations with dedicated software.
 30
1. The students prepare individually for laboratory classes. 2. The students execute the project in a group or individually and prepare its documentation. 3. The students prepare multimedia presentations about the completed project and show them in front of the group.
 45 Project [W_001] Project presentation [W_002]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)