Advanced methods of image processing and analysis Field of study: Computer Science
Programme code: 08-S2INIA15.2016

Module name: Advanced methods of image processing and analysis
Module code: 08-IN-S2-ZMPiAO
Programme code: 08-S2INIA15.2016
Semester:
  • summer semester 2017/2018
  • winter semester 2017/2018
Language of instruction: English
Form of verification: course work
ECTS credits: 3
Description:
Content of the module: advanced methods of image processing and analysis requires assimilation and understanding of theoretical bases and acquiring practical skills of this knowledge use. Theoretical bases are, among others – assimilation and understanding of basic notions connected with the subject, acquiring aptitude to associate and use of the discussed issues. It is also the skill of sufficiently effective and fast finding of the required information in literature. Practical skills are gained through analysis of example algorithms and individual tasks solving. Thus, the module constitutes a link between theoretical knowledge, general examples and the skill of the chosen methods (issues) and knowledge profiling in practical use.
Prerequisites:
(no information given)
Key reading:
(no information given)
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]
Performs individual and team works. [ZMPiAO -K_6]
 K_2_A_I_K01 [1/5]
Demonstrates responsibility for tasks realized together in a team. [ZMPiAO -K_7]
 K_2_A_I_K06 [1/5]
Solves tasks covering image recognition. [ZMPiAO -U_4]
 K_2_A_I_U01 [3/5]
Classifies existing IT solutions: applications, algorithms, etc. [ZMPiAO -U_5]
 K_2_A_I_U05 [1/5]
Classifies knowledge in the field of mathematics and digital signal processing. [ZMPiAO -W_1]
 K_2_A_I_W01 [1/5]
Explains basic methods, techniques, tools and materials uses in image recognition [ZMPiAO -W_2]
 K_2_A_I_W08 [2/5]
Classifies information from literature and other sources referring to image recognition. [ZMPiAO -W_3]
 K_2_A_I_W15 [2/5]
Type Description Codes of the learning outcomes of the module to which assessment is related
Test [ZMPiAO _w_1]
Within the module, three tests will be effected concerning subsequent stages of familiarizing with the module – neural networks, - distributed algorithms, - statistical methods. The student during all the three tests performs practical implementation of four given algorithms in Matlab environment.
 ZMPiAO -W_1 ZMPiAO -W_2
Short test [ZMPiAO _w_2]
Before classes, the student solves a given problem verifying assimilation of knowledge of the previous class.
 ZMPiAO -U_4 ZMPiAO -W_2
Project [ZMPiAO _w_3]
Within the module, three individual projects will be executed, which will refer to three basic sections: neural networks, distributed algorithms and statistical methods used in image recognition.
 ZMPiAO -K_6 ZMPiAO -K_7 ZMPiAO -U_5 ZMPiAO -W_1 ZMPiAO -W_2 ZMPiAO -W_3
Credit [ZMPiAO _w_4]
Credit in the form of test covering issues discussed during lectures and laboratory classes.
 ZMPiAO -K_6 ZMPiAO -K_7 ZMPiAO -U_5 ZMPiAO -W_1 ZMPiAO -W_2 ZMPiAO -W_3
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 [ZMPiAO _fs_1]
Discussing the basic methods of image recognition with special focus on methods using neural networks, distributed algorithms, statistical methods. Implementation of the chosen neural networks in Matlab software and execution of their accurateness verification. Creating a diagnostic pattern and discussing problems arising while comparing qualities of the obtained results. Implementation in Matlab software of the algorithm recognizing specific disease entities on the chosen image types.
 15
Student’s work with indicated field literature and lecture materials covering practical algorithms implementation and necessary theoretical bases. It concerns individual assimilation of the knowledge discussed during lecture.
 15 Short test [ZMPiAO _w_2] Project [ZMPiAO _w_3] Credit [ZMPiAO _w_4]
laboratory classes [ZMPiAO _fs_2]
The teacher, together with students analyzes algorithms discussed during lectures in practical implementation. The students individually solve the given problems referring to medical images recognition. During chosen classes, the student working in groups of three or four, obtains instructions to execute three projects.
30
Student is obliged to be prepared of theoretical knowledge acquired during lectures and present in gathered literature. Student executes three project tasks in a group, connected with practical algorithm implementation in Matlab software.
30 Test [ZMPiAO _w_1] Project [ZMPiAO _w_3]
Attachments
Module description (PDF)
Information concerning module syllabuses might be changed during studies.
Syllabuses (USOSweb)
Semester Module Language of instruction
(no information given)