Das Paper "Rebricking frames and bases" von Thomas Fink, Brigitte Forster und Florian Heinrich erscheint demnächst im Journal of Mathematical Analysis and Applications. 

Der Preprint liegt im  Arxiv unter

https://arxiv.org/abs/2306.15038

Abstract:

In 1949, Denis Gabor introduced the ``complex signal'' (nowadays called ``analytic signal'') by combining a real function f with its Hilbert transform Hf to a complex function f+iHf. His aim was to extract phase information, an idea that has inspired techniques as the monogenic signal and the complex dual tree wavelet transform. In this manuscript, we consider two questions: When do two real-valued bases or frames {fn:n∈ℕ} and {gn:n∈ℕ} form a complex basis or frame of the form {fn+ign:n∈ℕ}? And for which bounded linear operators A forms {fn+iAfn:n∈ℕ} a complex-valued orthonormal basis, Riesz basis or frame, when {fn:n∈ℕ} is a real-valued orthonormal basis, Riesz basis or frame? We call this approach \emph{rebricking}. It is well-known that the analytic signals don't span the complex vector space L2(ℝ;ℂ), hence H is not a rebricking operator. We give a full characterization of rebricking operators for bases, in particular orthonormal and Riesz bases, Parseval frames, and frames in general. We also examine the special case of finite dimensional vector spaces and show that we can use any real, invertible matrix for rebricking if we allow for permutations in the imaginary part.

Das Paper  "Stabilizing Tensor Voting for 3D Curvature Estimation" von  Victor Alfaro Pérez, Virginie Uhlmann, und Brigitte Forster-Heinlein erscheint demnächst in den Proceedings "Workshop on mathematical modeling and scientific computing". 

Abstract: Curvature plays an important role in the function of biological membranes, and is therefore a readout of interest in microscopy data. The PyCurv library established itself as a valuable tool for curvature estimation in 3D microscopy images. However, in noisy images, the method exhibits visible instabilities, which are not captured by the standard error measures. In this article, we investigate the source of these instabilities, provide adequate measures to detect them, and introduce a novel post-processing step which corrects the errors. We illustrate the robustness of our enhanced method over various noise regimes and demonstrate that with our orientation correcting post-processing step, the PyCurv library becomes a truly stable tool for curvature quantification.

Certainly interesting also for students with the aim of a doctoral thesis in the domain of AI.
Cheers, Brigitte Forster

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For the English invitation see below.
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Einladung
KI Campus Ostbayern: AI-Talk für Promovierende

Termin: Mittwoch, 27. November 2024, 14:00 – 17:30 Uhr, OTH Regensburg

Du beschäftigst dich in deiner Promotion mit dem Thema KI? Du suchst die Möglichkeit, dich zu deinem Dissertationsprojekt mit anderen Doktorandinnen und Doktoranden auszutauschen? Du möchtest dein Netzwerk zu Promovierenden im Fachgebiet der KI erweitern? Dann bist du beim „AI-Talk für Promovierende“genau richtig.

Das Format richtet sich an alle Nachwuchswissenschaftlerinnen und Nachwuchswissenschaftler an den ostbayerischen Hochschulen, die aktuell an ihrer Promotion im Bereich der künstlichen Intelligenz arbeiten. In der Veranstaltung am 27. November 2024 werden aktuelle KI-Promotionsprojekte vorgestellt und diskutiert. In einem anschließenden Vernetzungsformat kannst du neue Kontakte knüpfen und die Kooperationsmöglichkeiten im KI Campus Ostbayern nutzen.

Die Teilnahme an der Veranstaltung ist kostenlos, eine Anmeldung aus organisatorischen Gründen jedoch erforderlich und ab sofort über die Homepage des KI Campus Ostbayern möglich:
https://www.kico.bayern/veranstaltungen/veranstaltungskalender/detail/ai-talk-fuer-promovierende-2024

AI-Talk_Einladung_2024[1].pdf


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Invitation
KI Campus Ostbayern: AI-Talk for PhDs and doctoral candidates

Date: Wednesday, 27th of November 2024, 2:00 - 5:30 p.m., OTH Regensburg

Are you working on your PhD in the field of artificial intelligence? Are you looking for an opportunity to connect with other doctoral students and discuss your dissertation projects? Do you want to expand your network within the AI community? Then the "AI-Talk for PhD students" is the perfect event for you.

Join us at our networking event on November 27, 2024, designed for doctoral students pursuing their PhD in the field of artificial intelligence at universities in eastern Bavaria. During this event, current AI dissertation projects will be presented and discussed. Following the presentations, you will have the opportunity to network and explore collaboration possibilities within the KI Campus Ostbayern. We look forward to welcoming you to this event!

Participation in the event is free of charge and the registration is open from now on: https://www.kico.bayern/veranstaltungen/veranstaltungskalender/detail/ai-talk-fuer-promovierende-2024

We look forward to welcoming you to this event.

AI-Talk_Invitation_2024.pdf
 

Die virtuelle Veranstaltungsreihe „Digitale Methoden in der Forschung“ richtet sich an Nachwuchswissenschaftler. 

https://www.indigo-netzwerk.de/digitale-methoden-in-der-forschung-2025/
 

Programm