A5078455511- Neural Networks and Applications
- Optical Polarization and Ellipsometry
- Fault Detection and Control Systems
- Image and Signal Denoising Methods
- Spectroscopy and Laser Applications
- Spectroscopy and Chemometric Analyses
- Laser-Ablation Synthesis of Nanoparticles
- Orthopedic Surgery and Rehabilitation
- Medical Imaging and Analysis
- Scientific Measurement and Uncertainty Evaluation
- Atomic and Subatomic Physics Research
- Adaptive optics and wavefront sensing
- Advanced X-ray and CT Imaging
- Spectroscopy and Quantum Chemical Studies
- Stellar, planetary, and galactic studies
- Advanced Electrical Measurement Techniques
- Laser-induced spectroscopy and plasma
- Diamond and Carbon-based Materials Research
Johannes Gutenberg University Mainz
2020-2021
Helmholtz Institute Mainz
2021
GSI Helmholtz Centre for Heavy Ion Research
2021
Advanced Research Center for Nanolithography (Netherlands)
2018
Vrije Universiteit Amsterdam
2018
Amsterdam University of Applied Sciences
2018
Amsterdam University Medical Centers
2018
University of Amsterdam
2018
For wrist complaints related to motion, a 2-D radiograph or CT scan of the static may not always be considered diagnostic. 3-D motion imaging, i.e., multiple 3DCT scans in time (4DCT), enables quantifying carpal and comparing patterns affected with those healthy contralateral side. The accuracy precision method, however, is limited by noise artifacts. Although, technique promising existing literature, analysis has never been investigated systematically. In this paper, we introduce evaluate...
The measurement of the propulsion metallic microdroplets exposed to nanosecond laser pulses provides an elegant method for probing ablation pressure in a dense laser-produced plasma. We present measurements velocity over three decades driving Nd:YAG pulse energy and observe near-perfect power law dependence. Simulations performed with RALEF-2D radiation-hydrodynamic code are shown be good agreement above specific threshold energy. simulations highlight importance radiative losses which...
We present a new cavity-based polarimetric scheme for highly sensitive and time-resolved measurements of birefringence dichroism, linear circular, that employs rapidly pulsed single-frequency continuous wave (CW) laser sources extends current spectropolarimetric techniques. demonstrate how the use CW source allows gains in spectral resolution, signal intensity, data acquisition rate compared to traditional pulsed-based cavity ring-down polarimetry (CRDP). discuss particular CW-CRDP modality...
We present different computational approaches for the rapid extraction of signal parameters discretely sampled damped sinusoidal signals. compare time- and frequency-domain-based in terms their accuracy precision time required estimating frequencies such signals, observe a general trade-off between speed. Our motivation is precise analysis signals as these become relevant view recent experimental developments cavity-enhanced polarimetry ellipsometry, where scales are typically within ∼1 − 10...
Abstract In this work we demonstrate the use of neural networks for rapid extraction signal parameters discretely sampled signals. particular, dense autoencoder to extract interest from exponentially decaying signals and oscillations. By using a three-stage training method careful choice network size, are able retrieve relevant directly latent space at significantly improved rates compared traditional algorithmic signal-analysis approaches. We show that achievable precision accuracy analysis...
We present different computational approaches for the rapid extraction of signal parameters discretely sampled damped sinusoidal signals. compare time- and frequency-domain-based in terms their accuracy precision time required estimating frequencies such signals, observe a general trade-off between speed. Our motivation is precise analysis signals as these become relevant view recent experimental developments cavity-enhanced polarimetry ellipsometry, where scales are typically within...
In this work we demonstrate the use of neural networks for rapid extraction signal parameters discretely sampled signals. particular, dense autoencoder to extract interest from exponentially decaying signals and oscillations. By using a three-stage training method careful choice network size, are able retrieve relevant directly latent space at significantly improved rates compared traditional algorithmic signal-analysis approaches. We show that achievable precision accuracy analysis is...