|
|
Main menu for Browse IS/STAG
Course info
KKY / USVP
:
Course description
Department/Unit / Abbreviation
|
KKY
/
USVP
|
Academic Year
|
2023/2024
|
Academic Year
|
2023/2024
|
Title
|
Introduction to Machine Perception
|
Form of course completion
|
Exam
|
Form of course completion
|
Exam
|
Accredited / Credits
|
Yes,
6
Cred.
|
Type of completion
|
Combined
|
Type of completion
|
Combined
|
Time requirements
|
Lecture
4
[Hours/Week]
Tutorial
1
[Hours/Week]
|
Course credit prior to examination
|
Yes
|
Course credit prior to examination
|
Yes
|
Automatic acceptance of credit before examination
|
Yes in the case of a previous evaluation 4 nebo nic.
|
Included in study average
|
YES
|
Language of instruction
|
Czech
|
Occ/max
|
|
|
|
Automatic acceptance of credit before examination
|
Yes in the case of a previous evaluation 4 nebo nic.
|
Summer semester
|
0 / -
|
13 / -
|
1 / -
|
Included in study average
|
YES
|
Winter semester
|
0 / -
|
0 / -
|
0 / -
|
Repeated registration
|
NO
|
Repeated registration
|
NO
|
Timetable
|
Yes
|
Semester taught
|
Summer semester
|
Semester taught
|
Summer semester
|
Minimum (B + C) students
|
10
|
Optional course |
Yes
|
Optional course
|
Yes
|
Language of instruction
|
Czech
|
Internship duration
|
0
|
No. of hours of on-premise lessons |
|
Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
|
Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
|
Fundamental theoretical course |
No
|
Fundamental course |
Yes
|
Fundamental theoretical course |
No
|
Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
|
None
|
Preclusive courses
|
KKY/SVP and KKY/ZDO and KKY/ZDO-E
|
Prerequisite courses
|
N/A
|
Informally recommended courses
|
KKY/ZSUR
|
Courses depending on this Course
|
N/A
|
Histogram of students' grades over the years:
Graphic PNG
,
XLS
|
Course objectives:
|
The goal of the course is to present an overview of the basic knowledge of the machine perception, especially computer speech processing and computer vision.
|
Requirements on student
|
Coming to the exam will be conditioned by elaborating individual task from area of machine perception. This activity will be supported by written report. The exam will contain both written (test) and oral parts.
|
Content
|
Introduction to machine perception. Computer speech and computer vision. Speech processing for automatic speech recognition and synthesis. Automatic speech recognition. Automatic synthesis of speech. Voice dialogue systems. Speech understanding. Demonstration of speech technology tasks. Properties of image data. Processing of color information. Histograms. Image pre-processing - brightness modification, filtration, edge detection. Image pre-processing - geometric transformations, frequency analysis. Image segmentation, shape modifications. Image description methods. Image recognition. Demonstration of image processing and multi-modal human-machine communication tasks.
|
Activities
|
|
Fields of study
|
Studentům je k dispozici kurz v Google Classroom se všemi podstatnými informacemi a materiály.
|
Guarantors and lecturers
|
-
Guarantors:
Doc. Ing. Jindřich Matoušek, Ph.D. (100%),
-
Lecturer:
Ing. Miroslav Jiřík, Ph.D. (100%),
Doc. Ing. Jindřich Matoušek, Ph.D. (100%),
Prof. Ing. Josef Psutka, CSc. (100%),
Doc. Ing. Miloš Železný, Ph.D. (100%),
-
Tutorial lecturer:
Ing. Miroslav Jiřík, Ph.D. (100%),
Ing. Petr Neduchal, Ph.D. (100%),
Prof. Ing. Josef Psutka, CSc. (100%),
Ing. Luboš Šmídl, Ph.D. (100%),
Doc. Ing. Miloš Železný, Ph.D. (100%),
|
Literature
|
-
Basic:
Psutka, Josef. Komunikace s počítačem mluvenou řečí. Praha : Academia, 1995. ISBN 80-200-0203-0.
-
Basic:
Psutka, Josef. Mluvíme s počítačem česky. Praha : Academia, 2006. ISBN 80-200-1309-1.
-
Basic:
Šonka, Milan; Hlaváč, Václav. Počítačové vidění. Praha : Grada, 1992. ISBN 80-85424-67-3.
-
Extending:
Shapiro, Linda G.; Stockman, George C. Computer vision. Upper Saddle River : Prentice Hall, 2001. ISBN 0-13-030796-3.
-
Extending:
Sonka, Milan; Hlavac, Vaclav; Boyle, Roger. Image processing, analysis, and machine vision. Toronto : Thomson, 2008. ISBN 978-0-495-08252-1.
-
On-line library catalogues
|
Time requirements
|
All forms of study
|
Activities
|
Time requirements for activity [h]
|
Preparation for an examination (30-60)
|
45
|
Contact hours
|
52
|
Presentation preparation (report) (1-10)
|
10
|
Preparation for comprehensive test (10-40)
|
30
|
Individual project (40)
|
35
|
Total
|
172
|
|
Prerequisites
|
Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
disponovat základními znalostmi z lineární algebry, pravděpodobnosti a statistiky
|
absolvovat předmět Základy strojového učení a rozpoznávání (KKY/ZSUR) |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
programovat v některém z běžných programovacích jazyků |
používat aktivně matematické metody získané dřívějším studiem |
používat MATLAB |
dovede analytciky přemýšlet |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
N/A |
|
Learning outcomes
|
Knowledge - knowledge resulting from the course: |
vytypovávat oblasti pro nasazování systémů strojového vnímání prostředí a zároveň se podílet na jejich instalaci |
Skills - skills resulting from the course: |
prokazuje základní dovednosti v oblasti zpracování mluvené řeči (automatické rozpoznávání, počítačová syntéza, hlasový dialog) |
prokazuje základní dovednostmi v oblasti zpracování obrazové informace (počítačové vidění) |
Competences - competences resulting from the course: |
N/A |
N/A |
|
Assessment methods
|
Knowledge - knowledge achieved by taking this course are verified by the following means: |
Combined exam |
Seminar work |
Skills - skills achieved by taking this course are verified by the following means: |
Combined exam |
Skills demonstration during practicum |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
|
Teaching methods
|
Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Lecture with visual aids |
Self-study of literature |
Skills - the following training methods are used to achieve the required skills: |
Lecture |
Textual studies |
Seminar |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Seminar |
Self-study of literature |
|
|
|
|