Tootfinder

heise meets ... Richard Seidl gewinnt den Deutschen Preis für Software-Qualität
Softwareentwickler müssen mehr tun, um Vertrauen zu schaffen. Nur so könne Technologie ein brauchbares Werkzeug bleiben, um die Zukunft zu gestalten.

Ich war heute zusammen mit Giorgio Armani im Radio. Ok, fast: Wir beide waren *Thema* im Info3.
Auch im Beitrag mit mir ging es um den Tod. Den Tod der Anonymität im Internet. Und was Jugendschutz und e-ID damit zu tun haben.
Ab 4'05" jetzt zum Nachhören und dann etwas länger im Echo der Zeit um 18 Uhr in SRF1.
#Anonymität

🇺🇦 #NowPlaying on KEXP's #MiddayShow
tUnE-yArDs:
🎵 Water Fountain
#tUnEyArDs
https://tune-yards.bandcamp.com/track/water-fountain-1
https://open.spotify.com/track/57JgKwQ0W5nYvTP2UNcNKF

from my link log —
Code golfing a tiny graphics demo using maths and a pinch of insanity.
https://blog.pkh.me/p/45-code-golfing-a-tiny-demo-using-maths-and-a-pinch-of-insanity.html
saved 2025-09-29

Code golfing a tiny demo using maths and a pinch of insanity

Weekend #Plankton Factoid 🦠🦐
While crustaceans are common as #zooplankton, insects are very rare, but one group is found globally in freshwaters. Chaoborus (phantom midge or glassworm) spend the majority of their life as predaceous plankton, but are familiar to many when the adults emerge lake…

Team Westwood Solution for MIDOG 2025 Challenge
Tengyou Xu, Haochen Yang, Xiang 'Anthony' Chen, Hongyan Gu, Mohammad Haeri
https://arxiv.org/abs/2509.02600 https://

Team Westwood Solution for MIDOG 2025 Challenge
This abstract presents our solution (Team Westwood) for mitosis detection and atypical mitosis classification in the MItosis DOmain Generalization (MIDOG) 2025 challenge. For mitosis detection, we trained an nnUNetV2 for initial mitosis candidate screening with high sensitivity, followed by a random forest classifier ensembling predictions of three convolutional neural networks (CNNs): EfficientNet-b3, EfficientNet-b5, and EfficientNetV2-s. For the atypical mitosis classification, we trained an…

I love international #rugby. Still, every time I watch a match between a heavyweight and a 2nd- or 3rd-tier country, I can't help but be disgusted by the vast gulf, created solely by money and the refusal of those with it to share the wealth, separating the teams. I want to see Samoa or Spain or Uruguay play England or New Zealand or France with the realistic goal of doing more than scoring a try or a …

On space-time FEM for time-optimal control problems governed by parabolic equations with mixed and endpoints constraints
Huynh Khanh, Bui Trong Kien
https://arxiv.org/abs/2509.03207

On space-time FEM for time-optimal control problems governed by parabolic equations with mixed and endpoints constraints
In this paper, we consider a class of time-optimal control problems governed by linear parabolic equations with mixed control-state constraints and end-point constraints, and without Tikhonov regularization term in the objective function. By the finite element method, we discretize the optimal control problem to obtain a sequence of mathematical programming problems in finite-dimensional spaces. Under certain conditions, we show that the optimal solutions of the discrete problems converge to an…

People in the US have just had their brains fried by suburban myths. We walked from a Copenhagen subway station to visit friends living in some of that housing, then we walked with them and their kids to the nearby pasture-N-stuff. They don't even own a bicycle yet, but they're making plans.
Afterwards, two stops up the subway line we stopped in a mall to pick up some stuff my wife needed for work the next day.

RF-DETR for Robust Mitotic Figure Detection: A MIDOG 2025 Track 1 Approach
Piotr Giedziun, Jan So{\l}tysik, Mateusz G\'orczany, Norbert Ropiak, Marcin Przymus, Piotr Krajewski, Jaros{\l}aw Kwiecie\'n, Artur Bartczak, Izabela Wasiak, Mateusz Maniewski
https://arxiv.org/abs/2509.02599

RF-DETR for Robust Mitotic Figure Detection: A MIDOG 2025 Track 1 Approach
Mitotic figure detection in histopathology images remains challenging due to significant domain shifts across different scanners, staining protocols, and tissue types. This paper presents our approach for the MIDOG 2025 challenge Track 1, focusing on robust mitotic figure detection across diverse histological contexts. While we initially planned a two-stage approach combining high-recall detection with subsequent classification refinement, time constraints led us to focus on optimizing a single…