Artificial intelligence in computer graphics Field of study: Computer Science
Programme code: W4-S2IN19.2022

Module name: Artificial intelligence in computer graphics
Module code: W4-IN-S2-20-F-SIwGK
Programme code: W4-S2IN19.2022
Semester:
  • summer semester 2025/2026
  • winter semester 2025/2026
  • summer semester 2024/2025
  • winter semester 2024/2025
  • summer semester 2023/2024
  • winter semester 2023/2024
Language of instruction: Polish
Form of verification: course work
ECTS credits: 4
Description:
The aim of the course is to acquaint the student 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]
Knows evolutionary algorithms, neural networks and machine learning methods, understands optimization and control issues. He can determine the problem, find a solution, develop a mathematical model, apply selected algorithms artificial intelligence. [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]
Knows the rules of modeling 3D scenes, among others problems of physical environment simulation, motion planning, object detection, collision avoidance. [M_002]
 K_W04 [1/5] K_W05 [1/5] K_U02 [1/5] K_U04 [1/5] K_K01 [1/5]
Is able to work individually or in a team, understands the importance of intellectual honesty in their own activities and other people act ethically. He understands the need to constantly improve his competences. Is able to think in a creative way, form opinions on basic 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]
Implementation of a semester project in the field of learning outcomes adopted in the module.
 M_001 M_003
Project presentation [W_002]
Audiovisual presentation on the forum of a group of students, discussion of assumptions and adopted method of solving a specific problem, analysis and assessment of the implementation of the project goal.
 M_003
Test [W_003]
Test with open and closed 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]
Contents of module training with the use of audiovisual methods.
 15
Independent study of lecture topics and recommended literature.
 30 Test [W_003]
laboratory classes [Z_002]
Practical implementation of the training program in the form of tasks to be implemented. Classes are held using computer stations and appropriate software.
 30
1. Individual preparation for laboratory classes 2. Individual or multi-person group project execution and its documentation 3. Preparation of the presentation in audiovisual form about the completed project and its presentation on the forum of a group of students
 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)