Lehrveranstaltungsverzeichnis der Wahlfächer
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Praktikum Digitale Übertragung [PrDÜ] -
- Lecturer:
- Clemens Stierstorfer
- Details:
- Praktikum, 3 cred.h, certificate, ECTS: 2,5, nur Fachstudium
- Dates:
- block seminar 28.2.2022-4.3.2022 Mon, Tue, Wed, Thu, Fri, 8:00 - 19:00, 06.018
- Fields of study:
- WPF ICT-MA ab 1
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Multimedia Security Exercises [MMSecEx] -
- Lecturer:
- Christian Riess
- Details:
- Übung, 2 cred.h
- Dates:
- Thu, 16:15 - 17:45, 00.153-113 CIP
- Fields of study:
- WPF ICT-MA 1
- Prerequisites / Organisational information:
- The majority of the methods are applications of signal processing. Thus, it is recommended to bring prior basic knowledge either in signal processing, pattern recognition, image processing, or related fields. Additionally, it is important to bring basic programming knowledge, preferably in python.
- Keywords:
- Steganography, Watermarking, Multimedia Forensics, Data Hiding
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Multimedia Security [MMSec] -
- Lecturer:
- Christian Riess
- Details:
- Vorlesung, 2 cred.h, certificate
- Fields of study:
- WPF ICT-MA 1
- Prerequisites / Organisational information:
- The majority of the methods are applications of signal processing. Thus, it is recommended to bring prior basic knowledge either in signal processing, pattern recognition, image processing, or related fields. Additionally, it is important to bring basic knowledge in programming, preferably in python.
- Keywords:
- Steganography, Watermarking, Multimedia Forensics, Data Hiding, Copyright Protection
| | | | Thu | 08:15 - 09:45 | Übung 3 / 01.252-128 | |
Riess, Ch. | |
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Machine Learning: Advances [SemML-II] -
- Lecturers:
- Tobias Feigl, Christoffer Löffler, Christopher Mutschler
- Details:
- Seminar, 2 cred.h, ECTS: 5, Anmeldung mit Themenanfrage per E-Mail vor Beginn des Seminars; Die Themen werden nach dem Prinzip "Wer zuerst kommt, mahlt zuerst" verteilt.
- Dates:
- block seminar 5.3.2022-19.3.2022 Sat, 10:00 - 16:00, 02.134-113
Findet teilweise als Blockveranstaltung statt. Weitere Informationen finden Sie im StudOn-Kurs.
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Dieser Kurs richtet sich an Anfänger, die mit maschinellem Lernen nicht vertraut sind, oder an Studierende, die eine schnelle Auffrischung suchen.
Anmeldung via e-mail an tobias.feigl@fau.de
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Maschinelles Lernen und Datenanalytik für Industrie 4.0 [MADI40] -
- Lecturers:
- Björn Eskofier, An Nguyen, Johannes Roider, Christoph Scholl
- Details:
- Seminar, 2 cred.h, graded certificate, ECTS: 5, nur Fachstudium, Registration via mail to johannes.roider@fau.de
- Dates:
- Wed, 16:15 - 18:00, 00.010
Starts October 20th 2021
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Prerequisites
Registration via e-mail to johannes.roider@fau.de Registration period: 16.08. - 19.10.2021
The seminar is planned to be held in person, given that the Bavarian state government allows face-to-face teaching at the time when the course starts. More information will be sent via mail to registered students. Requirements:
Prior knowledge of machine learning via courses like PA, IntroPR, PR, DL, MLTS, CVP or equivalent (ideally first project experiences) is expected! Motivation to explore scientific findings (e.g. via literature research) Motivation to code and analyze data
Examination:
50% of grade: Presentation + demo (20 minutes)
50% of grade 4 pages IEEE standard paper (excluding references) (+ code submission)
Attending the presentations of other students
- Keywords:
- Machine Learning, Data Analytics, Process Mining, Predictive Maintenance, Industry 4.0, Healthcare
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AI-enabled wireless networks [AInet] -
- Lecturer:
- Mehdi Harounabadi
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 2,5
- Dates:
- Fri, 15:00 - 16:30, 00.151-113
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Rapid growth in the number of connected wireless nodes such as mobile phones, low power IoT devices, connected vehicles, etc. will expand the scale of the next generation of wireless and mobile networks. Moreover, the foreseen use cases like connected autonomous vehicles, smart homes and cities, ultra-fast and reliable industrial wireless networks, etc. will require ultra-low latency and highly reliable communication. Existing and traditional algorithms are not feasible for the optimization and management of such networks to fulfill the requirements of the emerging use cases due to their high complexity, high dynamicity, and the massive amount of the generated data by connected devices. Recently, artificial intelligence (AI) is planned to be utilized as a new paradigm for the design, development and optimization of the next generation wireless and mobile networks. Machine learning (ML) as a subset of AI will be applied to develop intelligent wireless nodes and infrastructures to address the demands of future use cases.
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Advanced Networking [AdN] -
- Lecturer:
- Kai-Steffen Jens Hielscher
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 2,5
- Dates:
- Tue, 14:15 - 15:45, 01.019
- Fields of study:
- WF ICT-MA ab 1
- Keywords:
- SDN, NFV, IoT, Cloud Computing, Fog Computing
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Computational Visual Perception [CompVP] -
- Lecturers:
- Bernhard Egger, Andreas Kist, Patrick Krauß, Andreas Maier, Tim Weyrich
- Details:
- Vorlesung, 4 cred.h, ECTS: 2,5, nur Fachstudium
- Dates:
- Tue, 12:15 - 13:45, 01.151-128
Wed, 10:15 - 11:45, 01.151-128
- Fields of study:
- WF ICT-MA ab 1
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Music Processing - Synthesis [MPS] -
- Lecturer:
- Maximilian Schäfer
- Details:
- Vorlesung, 2 cred.h, graded certificate, credit: 2/2, nur Fachstudium
- Dates:
- Thu, 8:15 - 9:45, 05.025
The lecture will be offered via a live Zoom session.
- Fields of study:
- WF ICT-MA 1-4
- Prerequisites / Organisational information:
- Voraussetzung sind Kenntnisse in digitaler Signalverarbeitung, Kenntnisse aus der Vorlesung Mensch-Maschine-Schnittstelle sind hilfreich, aber nicht notwendig.
Die Vorlesung ist thematisch eng verwandt mit der Vorlesung "Music Processing - Analysis" von Prof. Meinard Müller. Beide Vorlesungen können jedoch unabhängig voneinander gehört werden.
Die Vorlesung wird in Live Sessions via Zoom stattfinden.
- Keywords:
- Audio, Signal Processing, Sound Synthesis, Computer Music
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Radar Signal Processing [RSP] -
- Lecturer:
- Gerhard Krieger
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 5
- Dates:
- Wed, 14:00 - 15:30, room tbd
Achtung: Raum 0.144; Cauerstr. 6
- Fields of study:
- WF ICT-MA 1-4
- Prerequisites / Organisational information:
Alle Informationen, Vorlesungs- und Übungsaufzeichnungen/Webinare und Materialien stehen auf StudOn zur Verfügung.
Bitte treten Sie dafür dem StudOn-Kurs „LHFT - Radar Signal Processing" bei.Keine formalen Voraussetzungen, aber grundlegende Kenntnisse erforderlich in Signal- und Systemtheorie, Wahrscheinlichkeitstheorie und linearer Algebra. Von Vorteil wären zudem Vorkenntnisse auf einem Teil der folgenden Gebiete: statistische Signalverarbeitung, Hochfrequenztechnik, Radar und/oder nachrichtentechnische Systeme. - Keywords:
- Radar Signalprocessing Signalverarbeitung
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Visual Computing in Medicine 1 [VCMed1] -
- Lecturers:
- Peter Hastreiter, Thomas Wittenberg
- Details:
- Vorlesung, 2 cred.h, certificate, ECTS: 2,5, nur Fachstudium, vormals "Analyse und Visualisierung medizinischer Bilddaten" (AnVisMed)
- Dates:
- Thu, 10:15 - 11:45, 02.019
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Fachstudium / Erwerb eines Scheins nach mündlicher Prüfung
- Keywords:
- Medizinische Visualisierung (Medical imaging), Segmentierung (Segmentation), Registrierung (Registration)
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Wissenschaftliches Arbeiten in den Ingenieur- und Naturwissenschaften [VORL WAIN] -
- Lecturer:
- Jens Kirchner
- Details:
- Vorlesung, 2 cred.h, certificate, ECTS: 2,5, für Anfänger geeignet
- Dates:
- Tue, 12:15 - 13:45, EL 4.14
Lehrveranstaltung erfolgt in teils digitaler Form und teils in Präsenz.
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Für die Teilnahme an der Vorlesung ist die Anmeldung im StudOn-Kurs notwendig: https://www.studon.fau.de/crs4046156.html
Für weitere Informationen über die Vorlesung siehe das in StudOn hinterlegte pdf: https://www.studon.fau.de/file4087742_download.html
- Keywords:
- Nicht-technisches Wahlfach, Softskills, Recherche, Vortrag, Präsentation, Publikation
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Designing Gamified Systems (@EELISA) [GamEU] -
- Lecturers:
- Benedikt Morschheuser, Gastredner, Tutoren
- Details:
- Vorlesung mit Übung, 4 cred.h, ECTS: 5, für Anfänger geeignet, geeignet als Schlüsselqualifikation, This course has reserved places for international European EELISA students: https://eelisa.eu
- Fields of study:
- WF ICT-MA ab 1
- Keywords:
- Gamification, Interactive Information Systems, HCI, Customer Engagement, Social Computing, Hedonic Systems, Games, EELISA
| | | | Thu | 13:15 - 14:45, 15:00 - 16:30 | Zoom-Meeting | |
Morschheuser, B.
Gastredner | |
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