SubjectsSubjects(version: 901)
Course, academic year 2021/2022
  
Selected topics in Computer Vision - NPGR041
Title: Vybrané kapitoly z počítačového vidění
Guaranteed by: Department of Software and Computer Science Education (32-KSVI)
Faculty: Faculty of Mathematics and Physics
Actual: from 2021 to 2021
Semester: both
E-Credits: 5
Hours per week, examination: 2/2 C+Ex [hours/week]
Capacity: unlimited
Min. number of students: unlimited
Virtual mobility / capacity: no
State of the course: taught
Language: Czech
Teaching methods: full-time
Note: you can enroll for the course in winter and in summer semester
Guarantor: doc. RNDr. Elena Šikudová, Ph.D.
Annotation -
Last update: doc. RNDr. Pavel Töpfer, CSc. (25.05.2020)
The lecture is focused on selected topics of computer vision. The graduate will master the advanced techniques of computer vision, image processing and recognition, such as feature extraction from the image, HDR, etc.
Course completion requirements -
Last update: doc. RNDr. Elena Šikudová, Ph.D. (26.05.2020)

http://cgg.mff.cuni.cz/~sikudova/#teaching

Literature -
Last update: doc. RNDr. Pavel Töpfer, CSc. (25.05.2020)

Mark Nixon Alberto Aguado: Feature Extraction and Image Processing for Computer Vision, 4th Edition, Academic Press

Trevor Hastie, Robert Tibshirani, Jerome Friedman: The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition, Springer

Elena Šikudová, Zuzana Černeková, Vanda Benešová, Zuzana Haladová, Júlia Kučerová: Počítačové videnie. Detekcia a rozpoznávanie objektov, vydavateľstvo Wikina, Praha

+ papers

Syllabus -
Last update: doc. RNDr. Pavel Töpfer, CSc. (25.05.2020)

Contrast and intensity manipulation, HDR, noise reduction, edge detection.

Global and local features for 2D object description.

Statistical pattern recognition, supervised and unsupervised learning, convolutional networks.

 
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