Zobrazeno 1 - 10
of 10 125
pro vyhledávání: '"Meinhardt, A"'
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
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
Federated Learning (FL) has garnered increasing attention due to its unique characteristic of allowing heterogeneous clients to process their private data locally and interact with a central server, while being respectful of privacy. A critical bottl
Externí odkaz:
http://arxiv.org/abs/2403.09904
Autor:
J. Sun, M. Hermann, K. Weinhold, M. Merkel, W. Birmili, Y. Yang, T. Tuch, H. Flentje, B. Briel, L. Ries, C. Couret, M. Elsasser, R. Sohmer, K. Wirtz, F. Meinhardt, M. Schütze, O. Bath, B. Hellack, V.-M. Kerminen, M. Kulmala, N. Ma, A. Wiedensohler
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 10667-10687 (2024)
As an important source of sub-micrometer particles, atmospheric new particle formation (NPF) has been observed in various environments. However, most studies provide little more than snapshots of the NPF process due to their underlying observations b
Externí odkaz:
https://doaj.org/article/727755de1a20464a84aab16d76896dec
Until recently, the Video Instance Segmentation (VIS) community operated under the common belief that offline methods are generally superior to a frame by frame online processing. However, the recent success of online methods questions this belief, i
Externí odkaz:
http://arxiv.org/abs/2308.15266
Autor:
Maximov, Maxim, Meinhardt, Tim, Elezi, Ismail, Papakipos, Zoe, Hazirbas, Caner, Ferrer, Cristian Canton, Leal-Taixé, Laura
The advent of data-driven technology solutions is accompanied by an increasing concern with data privacy. This is of particular importance for human-centered image recognition tasks, such as pedestrian detection, re-identification, and tracking. To h
Externí odkaz:
http://arxiv.org/abs/2306.11710