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Image Analysis II

Image Analysis II
460-4107/01
čeština Image Analysis II
460-4107/02
angličtina

Summary

The following topics are covered: Modern methods of object detection and object recognition. Typically, the approaches are based on the image descriptors that are combined with the machine learning methods. The principles and aplications of deep learning and convolutional neural networks are also covered (detection of vehicles, pedestrians, faces).

Literature

1. Chollet, F.: Deep Learning with Python. Manning, ISBN-13: 978-1617294433 , 2017
2. Gonzalez, R. C., Woods, R. E.: Digital image processing, New York, NY: Pearson, ISBN-13: 978-0133356724 , 2018
3. Zhang, A., Lipton, Z.C., Li, M., Smola, A.J.: Dive into Deep Learning, https://d2l.ai, 2020

Advised literature

1. Burger, W., Burge, M., J.: Principles of Digital Image Processing: Fundamental Techniques, Springer, ISBN-10: 1848001908 , ISBN-13: 978-1848001909 , 2011
2. Brahmbhatt, S.: Practical OpenCV (Technology in Action), Apress, ISBN-10: 1430260793 , ISBN-13: 978-1430260790 , 2013
3. Gary Bradski, Adrian Kaehler: Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library, O'Reilly Media, 2017


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Language of instruction čeština, angličtina
Code 460-4107
Abbreviation ANO II
Course title Image Analysis II
Coordinating department Department of Computer Science
Course coordinator Ing. Radovan Fusek, Ph.D.