Tootfinder

Inducing ferromagnetism by structural engineering in a strongly spin-orbit coupled oxide
Ji Soo Lim, Carmine Autieri, Merit Spring, Martin Kamp, Amar Fakhredine, Pavel Potapov, Daniel Wolf, Sergii Pylypenko, Axel Lubk, Johannes Schultz, Nicolas Perez, B\"orge Mehlhorn, Louis Veyrat, Mario Cuoco, Fadi Choueikan, Philippe Ohresser, Bernd B\"uchner, Giorgio Sangiovanni, Ralph Claessen, Michael Sing

Inducing ferromagnetism by structural engineering in a strongly spin-orbit coupled oxide
Magnetic materials with strong spin-orbit coupling (SOC) are essential for the advancement of spin-orbitronic devices, as they enable efficient spin-charge conversion, complex magnetic structures, spin-valley physics, topological phases and other exotic phenomena. 5d transition-metal oxides such as SrIrO3 feature large SOC, but usually show paramagnetic behavior due to broad bands and a low density of states at the Fermi level, accompanied by a relatively low Coulomb repulsion. Here, we unveil …

Ever wondered how Kubernetes runs on a tractor? At Berlin Buzzwords 2025, join Wieneke Keller & Sebastian Lenartowicz from Aurea Imaging to explore their innovative AgTech journey! Discover how they built an edge device with Python microservices and K3s for precision farming, tackling unique rural challenges. 
Learn more:

Precision farming powered by K3s and TensorRT
Aurea Imaging is an AgTech scaleup focusing on precision farming in orchards. By retrofitting our TreeScout sensor package to their tractors, farmers are able to collect data about their orchard down to the tree level as they perform other tasks. Using onboard stereo cameras, the tractor’s high-precision GPS, a machine-vision pipeline running in real time on the device, and cloud-based analytics, this data is turned into maps used by other agricultural machines that enable the grower to utili…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/5]:
- 3D Hierarchical Panoptic Segmentation in Real Orchard Environments Across Different Sensors
Sodano, Magistri, Marks, Hosn, Zurbayev, Marcuzzi, Malladi, Behley, Stachniss

Adaptive Per-Tree Canopy Volume Estimation Using Mobile LiDAR in Structured and Unstructured Orchards
Ali Abedi, Fernando Cladera, Mohsen Farajijalal, Reza Ehsani
https://arxiv.org/abs/2506.08061

Adaptive Per-Tree Canopy Volume Estimation Using Mobile LiDAR in Structured and Unstructured Orchards
We present a real-time system for per-tree canopy volume estimation using mobile LiDAR data collected during routine robotic navigation. Unlike prior approaches that rely on static scans or assume uniform orchard structures, our method adapts to varying field geometries via an integrated pipeline of LiDAR-inertial odometry, adaptive segmentation, and geometric reconstruction. We evaluate the system across two commercial orchards, one pistachio orchard with regular spacing and one almond orchard…

View on the low lands, from the water tower near the village of Werkhoven, the Netherlands.

I come from the land of the fog

Att folk orkar 🤷🏼‍♂️🙂
Men are shaving off their eyelashes on TikTok. https://theconversation.com/men-are-shaving-off-their-eyelashes-on-tiktok-heres-why-that-might-be-a-bad-idea-256222

Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards
David Rapado-Rincon, Gert Kootstra
https://arxiv.org/abs/2507.12093 h…

Tree-SLAM: semantic object SLAM for efficient mapping of individual trees in orchards
Accurate mapping of individual trees is an important component for precision agriculture in orchards, as it allows autonomous robots to perform tasks like targeted operations or individual tree monitoring. However, creating these maps is challenging because GPS signals are often unreliable under dense tree canopies. Furthermore, standard Simultaneous Localization and Mapping (SLAM) approaches struggle in orchards because the repetitive appearance of trees can confuse the system, leading to mapp…

#silentsunday oder doch #independentsday?

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Scowl:
🎵 Not Hell, Not Heaven
#Scowl
https://scowl831.bandcamp.com/track/not-hell-not-heaven
https://open.spotify.com/track/3Dv3zgW4OHauERx9RIZUXL