Zobrazeno 1 - 10
of 13 323
pro vyhledávání: '"Meinhardt"'
Autor:
Meinhardt, Hanna
Die Anzahl der Demenzerkrankten steigt jährlich an. Durch Demenzdörfer wird ihnen die Möglichkeit gegeben, ihren Alltag möglichst realistisch nachzugehen. Sie sind speziell für Menschen mit Demenz ausgerichtet und auf integrative Wohngemeinschaf
Autor:
Herb, Konstantin, Völker, Laura A., Abendroth, John M., Meinhardt, Nicholas, van Schie, Laura, Gambardella, Pietro, Degen, Christian L.
Quantum magnetometers based on spin defects in solids enable sensitive imaging of various magnetic phenomena, such as ferro- and antiferromagnetism, superconductivity, and current-induced fields. Existing protocols primarily focus on static fields or
Externí odkaz:
http://arxiv.org/abs/2411.05542
Autor:
Hua, Lingyang, Alkhatib, Majd, Podlesek, Dino, Günther, Leila, Pinzer, Thomas, Meinhardt, Matthias, Zeugner, Silke, Herold, Sylvia, Cahill, Daniel P., Brastianos, Priscilla K., Williams, Erik A., Clark, Victoria E., Shankar, Ganesh M., Wakimoto, Hiroaki, Ren, Leihao, Chen, Jiawei, Gong, Ye, Schackert, Gabriele, Juratli, Tareq A.
Spinal meningiomas (SM) comprise 5–10% of primary meningiomas and up to 30% of spinal intradural tumors. SMs are usually sporadic, but rarely, they can develop in association with genetic diseases like neurofibromatosis type 2 or schwannomatosis [2
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A91047
https://tud.qucosa.de/api/qucosa%3A91047/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A91047/attachment/ATT-0/
Histological slides are an important tool in the diagnosis of tumors as well as of other diseases that affect cell shapes and distributions. Until now, the research concerning an optimal staining time has been mainly done empirically. In experimental
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A91381
https://tud.qucosa.de/api/qucosa%3A91381/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A91381/attachment/ATT-0/
Autor:
Steiner, Gerald, Galli, Roberta, Preusse, Grit, Michen, Susanne, Meinhardt, Matthias, Temme, Achim, Sobottka, Stephan B., Juratli, Tareq A., Koch, Edmund, Schackert, Gabriele, Kirsch, Matthias, Uckermann, Ortrud
Purpose: Infrared (IR) spectroscopy has the potential for tumor delineation in neurosurgery. Previous research showed that IR spectra of brain tumors are generally characterized by reduced lipid-related and increased protein-related bands. Therefore,
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A89286
https://tud.qucosa.de/api/qucosa%3A89286/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A89286/attachment/ATT-0/
In the recent paradigm of Federated Learning (FL), multiple clients train a shared model while keeping their local data private. Resource constraints of clients and communication costs pose major problems for training large models in FL. On the one h
Externí odkaz:
http://arxiv.org/abs/2405.20623
Autor:
Tönnies, Florian, Brown, Adam, Kiyim, Baris, Kuger, Fabian, Lindemann, Sebastian, Meinhardt, Patrick, Schumann, Marc, Stevens, Andrew
The largest direct dark matter search experiments to date employ dual-phase time projection chambers (TPCs) with liquid noble gas targets. These detect both the primary photons generated by particle interactions in the liquid target, as well as propo
Externí odkaz:
http://arxiv.org/abs/2405.10687
Increasing the annotation efficiency of trajectory annotations from videos has the potential to enable the next generation of data-hungry tracking algorithms to thrive on large-scale datasets. Despite the importance of this task, there are currently
Externí odkaz:
http://arxiv.org/abs/2404.11426
Autor:
Di Piazza, Theo, Meinhardt-Llopis, Enric, Facciolo, Gabriele, Bascle, Benedicte, Abgrall, Corentin, Devaux, Jean-Clement
We propose a novel method for geolocalizing Unmanned Aerial Vehicles (UAVs) in environments lacking Global Navigation Satellite Systems (GNSS). Current state-of-the-art techniques employ an offline-trained encoder to generate a vector representation
Externí odkaz:
http://arxiv.org/abs/2404.06207
Autor:
Ošep, Aljoša, Meinhardt, Tim, Ferroni, Francesco, Peri, Neehar, Ramanan, Deva, Leal-Taixé, Laura
We propose the SAL (Segment Anything in Lidar) method consisting of a text-promptable zero-shot model for segmenting and classifying any object in Lidar, and a pseudo-labeling engine that facilitates model training without manual supervision. While t
Externí odkaz:
http://arxiv.org/abs/2403.13129