TY  - JOUR
A1  - Hartung, Frank
A1  - Kesici, Sinan
A1  - Catrein, Daniel
T1  - DRM protected Dynamic Adaptive HTTP Streaming
JF  - Proceedings of the 2011 ACM Multimedia Systems Conference [Elektronische Ressource] : February 23 - 25, 2011, San Jose, CA, USA / sponsored by: ACM SIGMM
Y1  - 2011
SN  - 9781450305181
N1  - ACM Multimedia Systems Conference ; (2 : ; 2011.02.23-25 : ; San Jose, Calif.)
SP  - 277
EP  - 282
PB  - ACM
CY  - New York, NY
ER  - 
TY  - JOUR
A1  - Hartung, Frank
A1  - Husoy, J. H.
T1  - Wavelet and subband coding of images - A comparative study / Hartung, F. ; Husoy, J. H.
JF  - Mathematical imaging: wavelet applications in signal and image processing : 15 - 16 July 1993, San Diego, California / sponsored and publ. by SPIE - the International Society for Optical Engineering. Andrew F. Laine, chair/ed
Y1  - 1993
SN  - 081941283X
N1  - SPIE proceedings series ; 2034 ; Society of Photo-Optical Instrumentation Engineers ; Conference ; (1993.07.15-16 : ; San Diego, Calif.)
SP  - 242
EP  - 253
PB  - SPIE
CY  - Bellingham, Wash.
ER  - 
TY  - CHAP
A1  - Hartung, Frank
A1  - Hillgärtner, Michael
A1  - Schmitz, Günter
A1  - Schuba, Marko
A1  - Adolphs, Fabian
A1  - Hoffend, Jens
A1  - Theis, Jochen
T1  - IT-Sicherheit im Automobil
T2  - AmE 2014 : Automotive meets Electronics, Beiträge der 5. GMM-Fachtagung vom 18. bis 19. Februar 2014 in Dortmund. (GMM-Fachbericht ; 78)
Y1  - 2014
SN  - 978-3-8007-3580-8
SP  - CD-ROM
PB  - VDE-Verl.
CY  - Berlin
ER  - 
TY  - CHAP
A1  - Dinghofer, Kai
A1  - Hartung, Frank
T1  - Analysis of Criteria for the Selection of Machine Learning Frameworks
T2  - 2020 International Conference on Computing, Networking and Communications (ICNC)
N2  - With the many achievements of Machine Learning in the past years, it is likely that the sub-area of Deep Learning will continue to deliver major technological breakthroughs [1]. In order to achieve best results, it is important to know the various different Deep Learning frameworks and their respective properties. This paper provides a comparative overview of some of the most popular frameworks. First, the comparison methods and criteria are introduced and described with a focus on computer vision applications: Features and Uses are examined by evaluating papers and articles, Adoption and Popularity is determined by analyzing a data science study. Then, the frameworks TensorFlow, Keras, PyTorch and Caffe are compared based on the previously described criteria to highlight properties and differences. Advantages and disadvantages are compared, enabling researchers and developers to choose a framework according to their specific needs.
Y1  - 2020
U6  - https://doi.org/10.1109/ICNC47757.2020.9049650
N1  - 2020 International Conference on Computing, Networking and Communications (ICNC), 17-20 February 2020, Big Island, HI, USA
SP  - 373
EP  - 377
PB  - IEEE
CY  - New York, NY
ER  - 
TY  - CHAP
A1  - Galdi, Chiara
A1  - Hartung, Frank
A1  - Dugelay, Jean-Luc
T1  - Socrates: A database of realistic data for source camera recognition on smartphones
T2  - Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM
Y1  - 2019
SN  - 978-989-758-351-3
U6  - https://doi.org/10.5220/0007403706480655
SP  - 648
EP  - 655
ER  - 
TY  - CHAP
A1  - Galdi, Chiara
A1  - Hartung, Frank
A1  - Dugelay, Jean-Luc
T1  - Videos versus still images: Asymmetric sensor pattern noise comparison on mobile phones
T2  - Electronic Imaging
N2  - Nowadays, the most employed devices for recoding videos or capturing images are undoubtedly the smartphones. Our work investigates the application of source camera identification on mobile phones. We present a dataset entirely collected by mobile phones. The dataset contains both still images and videos collected by 67 different smartphones. Part of the images consists in photos of uniform backgrounds, especially collected for the computation of the RSPN. Identifying the source camera given a video is particularly challenging due to the strong video compression. The experiments reported in this paper, show the large variation in performance when testing an highly accurate technique on still images and videos.
KW  - Image Forensics
KW  - Mobile Phones
KW  - Image Database
Y1  - 2017
U6  - https://doi.org/10.2352/ISSN.2470-1173.2017.7.MWSF-331
SN  - 2470-1173
N1  - IS&T International Symposium on Electronic Imaging 2017
Media Watermarking, Security, and Forensics 2017
SP  - 100
EP  - 103
PB  - Society for Imaging Science and Technology
CY  - Springfield, Virginia
ER  - 
TY  - JOUR
A1  - Elsen, Ingo
A1  - Hartung, Frank
A1  - Horn, Uwe
A1  - Kampmann, Markus
A1  - Peters, Liliane
ED  - Voas, Jeffrey
T1  - Streaming technology in 3G mobile communication systems
JF  - Computer : innovative technology for computer professionals
N2  - Third-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality Internet content that meets the specific needs of the rapidly growing mobile market.
Y1  - 2001
SN  - 0018-9162
SN  - 1558-0814
VL  - 34
IS  - 9 Seiten
SP  - 46
EP  - 52
PB  - IEEE
CY  - New York
ER  -