Towards Trustworthy AI in Dentistry
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...
Federated Learning in Dentistry: Chances and Challenges
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...
Optical Generation and Transmission of mmWave Signals in 5G ERA: Experimental Evaluation Paradigm
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...
Measurably Stronger Explanation Reliability Via Model Canonization
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...
History Dependent Significance Coding for Incremental Neural Network Compression
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...
To Pretrain or Not? A Systematic Analysis of the Benefits of Pretraining in Diabetic Retinopathy
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...
Ultrawideband Systems and Networks: Beyond C+L -Band
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...
Hyperspectral Demosaicing of Snapshot Camera Images Using Deep Learning
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...
Experimental Investigation of Information Bit Scrambling for Physical-Layer Security in Coherent Fiber-Optic Systems
We experimentally demonstrate tap-proof coherent optical 640-Gb/s transmission based on encryption-less physical layer security. Information bit scrambling combined with soft-decision error-correction coding yields favorably small security gaps,...
Advanced DSP-based Monitoring for Spatially resolved and Wavelength-dependent Amplifier Gain Estimation and Fault Location in C+L-band Systems
We study the benefits of applying advanced DSP-based monitoring on multiple wavelength division multiplexing (WDM) channels allocated in the optical grid to infer wavelength-wise characteristics of a C+L-band optical line system. In that context,...