Coaching mistakes in the final seconds cost the Cowboys against the Ravens https://www.foxsports.com/articles/nfl/coaching-mistakes-in-the-final-seconds-cost-the-cowboys-against-the-ravens
SXSW plans to add a dedicated podcast festival in 2027, making it a core element of the event, alongside Film & TV, Music, Comedy, and the Innovation Conference (Matt Grobar/Deadline)
https://deadline.com/2026/08/sxsw-launching-podcast-festival-2027-12370435…
Mit dem Mietauto 2x quer durch die zweitgrößte Stadt Griechenlands zu fahren war heute wirklich mal ein anderes Level an Herausforderung.
Ich möchte nicht sagen, dass es keinen Spaß gemacht hat - ich mag das. Doch ich gebe zu, dass es sehr anstrengend war.
Es hat sich aber gelohnt, wir haben viel gesehen.
#CHinGR26
Hyperspectral Calibration Detection: A Novel Concept For Change Detection With Unsupervised Incremental Safe Pseudo-Labeling Implementation
Chia-Hsiang Lin, Shih-Min Hsu, Ching-Yun Liang, Jocelyn Chanussot, Jhih-Yan Chen
https://arxiv.org/abs/2608.06028 https://arxiv.org/pdf/2608.06028 https://arxiv.org/html/2608.06028
arXiv:2608.06028v1 Announce Type: new
Abstract: Hyperspectral change detection (HCD) has found numerous key applications, such as land cover monitoring. The majority of benchmark HCD algorithms are semi-supervised methods, and some of them can even achieve very low sample labeling rates. However, in some practical scenarios, such as those requiring immediate detection responses for onboard edge computing, we need to achieve the zero-label requirement as ground-truth labeling would not be available onboard for newly acquired images. In this work, we propose a fully unsupervised HCD algorithm, together with a lightweight model, quite suitable for onboard detection missions. Based on an iteratively augmented training set that safely collects some unchanged pixel samples, we learn an iteratively refined spectrum calibration function that eventually compensates the variability of acquisition conditions (often observed in bitemporal images), thereby making the changed pixels easily detectable by analyzing the calibrated spectra. The proposed hyperspectral looping unsupervised calibration and incremental detection (HyperLUCID) algorithm is not only computationally efficient (around 1 to 2 orders of magnitude faster than most benchmark HCD methods), but has also achieved state-of-the-art results (around 93.6% to 97.9% overall accuracy) on several real benchmark HCD datasets. Source codes: https://github.com/IHCLab/HyperLUCID.
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Im Grunde ist es ein gutes Zeichen, dass ich so wenig aus unserem #CHinGR26 Urlaub poste. Ich genieße die Zeit hier sehr, und habe schlicht keine Lust, auf dem Handy herumzutippen statt die traumhafte Aussicht zu genießen.
Fotos gibt's ab und an auf Instagram.
Bis bald! 🌴
Wenn ich Frostbeule nicht nur schon am ersten Tag im Meer schwimmen gehe, sondern ich sogar ohne zu zögern ins Wasser gehe und denke "Meine Güte, ist das warm!", dann ist wirklich Klima-Alarmstufe Rot!
#CHinGR26
From 'Ka-chow' to ka-ching: How Baker Mayfield found out about his new contract https://www.espn.com/nfl/story/_/id/49885155/tampa-bay-buccaneers-how-baker-mayfield-learned-new-contract-cars-movie
Auf der Terrasse unseres Zimmers über dem nächtlichen Mittelmeer 🤩
#CHinGR26