Lehrveranstaltungsverzeichnis der Wahlfächer
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Multimedia Security Exercises -
- 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(A)] -
- 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
| | | | Tue | 12:15 - 13:45 | Übung 3 / 01.252-128 | |
Riess, Ch. | |
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Digital Signal Processing Laboratory [PrDSV(RZ)] -
- Lecturers:
- Heinrich Löllmann, Matthias Kreuzer
- Details:
- Praktikum, 2 cred.h, certificate, nur Fachstudium, The course will be offered on Thursday morning (8:30-12:30) and Friday afternoon (14:00-18:00).
- Dates:
- Fri, 14:00 - 18:00, 06.021
Thu, 8:30 - 12:30, 06.021
The exact dates and format will be announced in due time.
- Fields of study:
- WF ICT-MA 1-4
- Prerequisites / Organisational information:
- Systemtheorie,
Digitale Signalverarbeitung
- Keywords:
- DSP
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Machine Learning and Data Analytics for Industry 4.0 -
- Lecturers:
- Björn Eskofier, Johannes Roider, Christoph Scholl, Lukas Schmidt
- Details:
- Seminar, 2 cred.h, graded certificate, ECTS: 5, nur Fachstudium, für FAU Scientia Gaststudierende zugelassen, Registration via mail to johannes.roider@fau.de
- Dates:
- Wed, 16:15 - 18:00, 00.010
Starts April 27th 2022
- Fields of study:
- WF ICT-MA ab 1
- Prerequisites / Organisational information:
- Registration via e-mail to johannes.roider@fau.de Registration period: 25.02.-04.05.2022
The seminar will be held face-to-face.
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
Please state your previous experience in machine learning (e. g. Which courses did you take? Which project experience do you have?) when registering for the course. Examination:
50% of grade: Presentation + demo (20 minutes)
50% of grade 4 pages IEEE standard paper (excluding references) (+ code submission)
Attendance of all meetings is required.
- Keywords:
- Machine Learning, Data Analytics, Process Mining, Predictive Maintenance, Industry 4.0, Healthcare, Automotive
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AI-enabled wireless networks [AInet(A)] -
- Lecturer:
- Mehdi Harounabadi
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 2,5
- Dates:
- Tue, 16:15 - 17:45, 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(A)] -
- Lecturer:
- Kai-Steffen Jens Hielscher
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 2,5
- Dates:
- Thu, 08:15 - 09:45, 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(A)] -
- Lecturers:
- Bernhard Egger, Andreas Kist, Patrick Krauß, Andreas Maier, Tim Weyrich
- Details:
- Vorlesung, 4 cred.h, ECTS: 2,5, nur Fachstudium
- Dates:
- Mon, Thu, 10:15 - 11:45, 00.152-113
- Fields of study:
- WF ICT-MA ab 1
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Music Processing - Synthesis [MPS(A)] -
- Lecturer:
- Maximilian Schäfer
- Details:
- Vorlesung, 2 cred.h, graded certificate, credit: 2/2, nur Fachstudium
- Dates:
- Thu, 08:15 - 09:45, 05.025
- 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(A)] -
- Lecturer:
- Gerhard Krieger
- Details:
- Vorlesung, 2 cred.h, graded certificate, ECTS: 5
- Dates:
- Wed, 16:15 - 17:45, HF-Technik: SR 05.222
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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Software-Projektmanagement -
- Lecturer:
- Bernd Hindel
- Details:
- Vorlesung, 4 cred.h, ECTS: 5, falls Sie sich nicht über StudOn zum Kurs anmelden können, wenden Sie sich bitte per eMail an Bernd.Hindel@BBH-Friedberg.de
- Dates:
- block seminar 6.3.2023-24.3.2023 Mon, Tue, Wed, Thu, Fri, 8:00 - 16:00, K2-119
- Fields of study:
- WF ICT-MA ab 1
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Visual Computing in Medicine 1 [VCMed1(A)] -
- Lecturers:
- Peter Hastreiter, Thomas Wittenberg
- Details:
- Vorlesung, 2 cred.h, certificate, ECTS: 2,5, nur Fachstudium, vormals "Analyse und Visualisierung medizinischer Bilddaten" (AnVisMed)
- Dates:
- Tue, 16:15 - 17:45, 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(A)] -
- Lecturer:
- Jens Kirchner
- Details:
- Vorlesung, 2 cred.h, certificate, ECTS: 2,5, für Anfänger geeignet
- Dates:
- Mon, 16:15 - 17:45, 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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