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Computer Vision (Lecture + Practice)

8.3068

Dozenten

Beschreibung

Prerequisites: Basic Math

Both the rapid growth of image and video data and new applications such as robotics require automated image processing. This course introduces the basic concepts of artificial vision.
Topics: Image acquisition and representation; mathematical background; basic point operations; linear and nonlinear filtering; morphological pattern recognition; color (perceptual aspects and technical representation); gray-, color- and texture-segmentation; image reconstruction and enhancement; object recognition; compression; applications (e.g., image search in databases). A focus is on object recognition, where topics range from simple edge based methods and template matching over traditional approaches like PCA over Boosting, SIFT and SURF to (deep) neural networks.

Weitere Angaben

Ort: 93/E31
Zeiten: Di. 14:00 - 16:00 (wöchentlich), Mi. 10:00 - 12:00 (wöchentlich), Do. 10:00 - 12:00 (wöchentlich)
Erster Termin: Dienstag, 25.10.2022 14:00 - 16:00, Ort: 93/E31
Veranstaltungsart: Vorlesung (Offizielle Lehrveranstaltungen)