Spline-Based Image-to-Volume Registration for Three-Dimensional Electron Microscopy

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This dataset accompanies the publication "Best practices in measuring absorption at the macro- and microscale" published in APL Photonics. The data can be used to reproduce original plots in figures 1-4 in the main text and all original plots in the suppor ...

A model is presented for simulating the electron beam within the entire gyrotron geometry using an electron optics code. The model incorporates the influence of the electromagnetic fields generated by the cavity's operational mode through a simple self-con ...

In this thesis, we study two closely related directions: robustness and generalization in modern deep learning. Deep learning models based on empirical risk minimization are known to be often non-robust to small, worst-case perturbations known as adversari ...

Chatter is a harmful self-excited vibration that commonly occurs during milling processes. Data -driven chatter detection and prediction is critical to achieve high surface quality and process efficiency. Most existing chatter detection approaches are base ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

Claude Debussy’s personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretabil ...

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

Recent advancements in deep learning have revolutionized 3D computer vision, enabling the extraction of intricate 3D information from 2D images and video sequences. This thesis explores the application of deep learning in three crucial challenges of 3D com ...

We present a statistical framework to benchmark the performance of reconstruction algorithms for linear inverse problems, in particular, neural-network-based methods that require large quantities of training data. We generate synthetic signals as realizati ...

This dataset originates from the DCML corpus initiative and contains musicological research data. For more information, please refer to its documentation page https://dcmlab.github.io/debussy_piano Please cite this dataset as Laneve, S., Schaerf ...

To obtain a more complete understanding of material microstructure at the nanoscale and to gain profound insights into their properties, there is a growing need for more efficient and precise methods that can streamline the process of 3D imaging using a tr ...

The present invention concerns an energy dispersion calibration method for calibrating an electron spectrometer of an electron spectrometer system including at least one electron emission source, electron optics and the electron spectrometer. The method co ...

The first measurements of the Fourier coefficients (V-n Delta) of the azimuthal distributions of charged hadrons emitted from photon-proton (gamma p) interactions are presented. The data are extracted from 68.8nb(-1) of ultra-peripheral proton-lead (pPb) c ...

We generalize and provide a linear algebra-based perspective on a finite element (FE) ho-mogenization scheme, pioneered by Schneider et al. (2017)[1] and Leuschner and Fritzen (2018)[2]. The efficiency of the scheme is based on a preconditioned, well-scale ...

Spline-Based Image-to-Volume Registration for Three-Dimensional Electron Microscopy

Chat with Graph Search

Dataset to accompany publication "Best practices in measuring absorption at the macro- and microscale"

Electron optics simulation in the overall gyrotron geometry

Understanding generalization and robustness in modern deep learning

Exploring the effectiveness of using internal CNC system signals for chatter detection in milling process

Enabling Uncertainty Estimation in Iterative Neural Networks

The diachronic development of Debussy’s musical style: a corpus study with Discrete Fourier Transform

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Advancing Self-Supervised Deep Learning for 3D Scene Understanding

A Statistical Framework to Investigate the Optimality of Signal-Reconstruction Methods

The Claude Debussy Solo Piano Corpus

3D reconstruction of curvilinear one-dimensional objects viewed in transmission electron microscopy

Electron spectrometer calibration method

Two-particle azimuthal correlations in γp interactions using pPb collisions at √sNN=8.16 TeV

An optimal preconditioned FFT-accelerated finite element solver for homogenization