|
|
Einrichtungen >> Technische Fakultät (TF) >> Department Informatik (INF) >> Lehrstuhl für Informatik 1 (IT-Sicherheitsinfrastrukturen) >>
|
Deep Learning in Multimedia Forensics (DLMFor)- Verantwortliche/Verantwortlicher
- PD Dr.-Ing. Christian Riess
- Angaben
- Praktikum
Präsenz
, ECTS-Studium, ECTS-Credits: 10, Sprache Englisch
Vorbesprechung: 28.10.2021, 16:00 - 18:00 Uhr
- Studienfächer / Studienrichtungen
- WF INF-BA-PR ab 3 (ECTS-Credits: 10)
WF INF-MA ab 1 (ECTS-Credits: 10)
WF AI-MA ab 1 (ECTS-Credits: 10)
- Voraussetzungen / Organisatorisches
- Participants must bring some practical experience in python.
Experience with the implementation of deep neural networks helps, but is not strictly necessary.
- Inhalt
- Subtle traces in the processing history of an image or video can provide a clue on the recording device, or whether some editing was applied. Multimedia forensics investigates methods to extract these traces from the data. Recent methods in multimedia forensics use deep learning to better adapt to data from the internet.
In this project, participants will gather practical experience with deep learning methods in multimedia forensics. Participants will implement published methods from scratch, and do own performance investigations on selected example inputs.
On the first meeting on October 28, groups of two students will be formed, and tasks will be distributed. During the project, there are regular consultation hours for status updates and programming support.
- ECTS-Informationen:
- Credits: 10
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 6, Maximale Teilnehmerzahl: 10
www: https://www.studon.fau.de/crs4138433.html
Für diese Lehrveranstaltung ist eine Anmeldung erforderlich.
Die Anmeldung erfolgt über: StudOn
- Verwendung in folgenden UnivIS-Modulen
- Startsemester WS 2021/2022:
- Deep Learning in Multimedia Forensics (DLMFor)
Kurse
|
 |
|
|
UnivIS ist ein Produkt der Config eG, Buckenhof |
|
|