Aktuelle Publikationen

Oktober 2022

Ultra-Broadband Optical Wavelength-Conversion using Nonlinear Multi-Modal Optical Waveguides

Norbert Hanik, Colja Schubert, Ronald Freund, Lars Zimmermann, Isaac Sackey, Gregor Ronniger, Tasnad Kernetzky, Yizhao Jia, Ulrike Höfler

Ultra-Broadband Wavelength Conversion is one of the key issues of future optical networks. The physical background of ultra-broadband optical wavelength conversion in a multi-modal Silicon waveguide and methods to optimize its functionality are...


Oktober 2022

Fixed 5th Generation Advanced and Beyond

F. J. Effenberger, D. Hillerkuss, I. Tomkos, Johannes K. Fischer, Mohammad Behnam Shariati, F. J. Effenberger, Yike Jiang, Thierno Diallo, Zhuotong Li, Wenhong Liu, Weizhao Yu, Yongli Zhao, Li Ao, Xiaobo Cao Cao, Qian Liu, Ming Jiang, Jialiang Jin, Junjie Li, Jian Tang, Anxu Zhang, Chengliang Zhang, Dezhi Zhang, Shikui Shen, Yue Sun, Xiongyan Tang, Guangquan Wang, Yuguang Chang, Raul Muñoz, Manny R. Estrada, Jorge Bonifacio, Marcus Brunner, Francis Keshmiri, Hongyu Li, Yi Lin, Xiang Liu, Frank Melinn, Jun Zhou, Qidong Zou, Steven Hill, Lloyd Mphahlele, Evandro Bender, Philippe Chanclou, Gaël Simon, Olivier Ferveur, Luca Pesando, Sandesh Manganahalli Jayaprakash, Marcel van Sambeek, Teun van der Veen, Oguzkagan Kanlidere

One of the overarching goals of the ETSI Industry Specification Group (ISG) F5G on Fifth Generation Fixed Network is to establish a regular rhythm of evolution for the fixed telecommunications network. So far, F5G has published technical...


Oktober 2022

Towards Trustworthy AI in Dentistry

Jackie Ma, Wojciech Samek, Sebastian Lapuschkin, Falk Schwendicke, Joachim Krois, Lisa Schneider, Reduan Achtibat, Martha Duchrau

Medical and dental artificial intelligence (AI) require the trust of both users and recipients of the AI to enhance implementation, acceptability, reach, and maintenance. Standardization is one strategy to generate such trust, with quality...


Oktober 2022

Federated Learning in Dentistry: Chances and Challenges

Roman Rischke, Karsten Müller, Wojciech Samek, Falk Schwendicke, Joachim Krois, Lisa Schneider

Building performant and robust artificial intelligence (AI)–based applications for dentistry requires large and high-quality data sets. Collaborative efforts are limited as privacy constraints forbid direct sharing across the borders of these...


Oktober 2022

To Pretrain or Not? A Systematic Analysis of the Benefits of Pretraining in Diabetic Retinopathy

Vignesh Srinivasan, Klaus-Robert Müller, Wojciech Samek, Alexander Binder, Nils Strodthoff, Jackie Ma

In this work, we aim to understand what type of pretraining works reliably in practice and what type of pretraining dataset is best suited to achieve good performance in small target dataset size scenarios. Considering diabetic retinopathy...


Oktober 2022

Optical Generation and Transmission of mmWave Signals in 5G ERA: Experimental Evaluation Paradigm

Efstathios Andrianopoulos, Christos Kouloumentas, Norbert Keil, David de Felipe Mesquida, Simon Nellen, Panos Groumas, Lefteris Gounaridis, Christos Tsokos, Tianwen Qian, Herkules Avramopoulos, Adam Raptakis, Nikolaos K. Lyras

We demonstrate the generation, of a mmWave signal via the injection of an optical frequency comb (OFC) into an integrated tunable dual distributed Bragg reflector (DBR) laser as well as the fiber transmission and the processing of this signal by...


Oktober 2022

History Dependent Significance Coding for Incremental Neural Network Compression

Gerhard Tech, Karsten Müller, Thomas Wiegand, Detlev Marpe, Heiko Schwarz, Heiner Kirchhoffer, Wojciech Samek, Jonathan Pfaff, Paul Haase, Daniel Becking

This paper presents an improved probability estimation scheme for the entropy coder of Incremental Neural Network Coding (INNC), which is currently under standardization in ISO/IEC MPEG. Major finding is that the probability of a significant...


Oktober 2022

Measurably Stronger Explanation Reliability Via Model Canonization

Franz Motzkus, Sebastian Lapuschkin, Leander Weber

Network canonization has recently been introduced, restructuring a neural network model into a functionally identical equivalent to which established explanation methods can be applied optimally. In this work, we quantitatively verify the...


Oktober 2022

Ultrawideband Systems and Networks: Beyond C+L -Band

Takeshi Hoshida, Johannes Fischer, Tomoyuki Kato, Vittorio Curri, Wladek Forysiak, Lidia Galdino, David T. Neilson, Pierluigi Poggiolini

In the evolution of optical networks, enhancement of spectral efficiency (SE) enhancement has been the most cost-efficient and thus the main driver for capacity enhancementincrease for decades. As a result, the development of optical transport...


Oktober 2022

Hyperspectral Demosaicing of Snapshot Camera Images Using Deep Learning

Eric Wisotzky, Peter Eisert, Anna Hilsmann, Charul Daudkhane

This work proposes a parallel neural network based demosaicing procedure for single-camera-one-shot-for hyperspectral imaging trained on a new ground truth dataset captured in a controlled environment by a hyperspectral snapshot camera with a 4×4...



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