Tootfinder

HASD: Hierarchical Adaption for pathology Slide-level Domain-shift
Jingsong Liu, Han Li, Chen Yang, Michael Deutges, Ario Sadafi, Xin You, Katharina Breininger, Nassir Navab, Peter J. Sch\"uffler
https://arxiv.org/abs/2506.23673

HASD: Hierarchical Adaption for pathology Slide-level Domain-shift
Domain shift is a critical problem for pathology AI as pathology data is heavily influenced by center-specific conditions. Current pathology domain adaptation methods focus on image patches rather than WSI, thus failing to capture global WSI features required in typical clinical scenarios. In this work, we address the challenges of slide-level domain shift by proposing a Hierarchical Adaptation framework for Slide-level Domain-shift (HASD). HASD achieves multi-scale feature consistency and comp…

Learning Approach to Efficient Vision-based Active Tracking of a Flying Target by an Unmanned Aerial Vehicle
Jagadeswara PKV Pothuri, Aditya Bhatt, Prajit KrisshnaKumar, Manaswin Oddiraju, Souma Chowdhury
https://arxiv.org/abs/2506.18264

Learning Approach to Efficient Vision-based Active Tracking of a Flying Target by an Unmanned Aerial Vehicle
Autonomous tracking of flying aerial objects has important civilian and defense applications, ranging from search and rescue to counter-unmanned aerial systems (counter-UAS). Ground based tracking requires setting up infrastructure, could be range limited, and may not be feasible in remote areas, crowded cities or in dense vegetation areas. Vision based active tracking of aerial objects from another airborne vehicle, e.g., a chaser unmanned aerial vehicle (UAV), promises to fill this important …

Just received a friend request on Facebook by someone named Peter Waldmeier.
https://www.facebook.com/peter.waldmeier.865
He seemed such a nice person, I think he is a model in a Scandinavian country.
When I asked him why he was sending me a friend request he go…

Model Predictive Path-Following Control for a Quadrotor
David Leprich, Mario Rosenfelder, Mario Hermle, Jingshan Chen, Peter Eberhard
https://arxiv.org/abs/2506.15447

Model Predictive Path-Following Control for a Quadrotor
Automating drone-assisted processes is a complex task. Many solutions rely on trajectory generation and tracking, whereas in contrast, path-following control is a particularly promising approach, offering an intuitive and natural approach to automate tasks for drones and other vehicles. While different solutions to the path-following problem have been proposed, most of them lack the capability to explicitly handle state and input constraints, are formulated in a conservative two-stage approach,…

Graphics4Science: Computer Graphics for Scientific Impacts
Peter Yichen Chen, Minghao Guo, Hanspeter Pfister, Ming Lin, William Freeman, Qixing Huang, Han-Wei Shen, Wojciech Matusik
https://arxiv.org/abs/2506.15786

Graphics4Science: Computer Graphics for Scientific Impacts
Computer graphics, often associated with films, games, and visual effects, has long been a powerful tool for addressing scientific challenges--from its origins in 3D visualization for medical imaging to its role in modern computational modeling and simulation. This course explores the deep and evolving relationship between computer graphics and science, highlighting past achievements, ongoing contributions, and open questions that remain. We show how core methods, such as geometric reasoning an…

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
Diana Nunes, Ricardo Amorim, Pedro Ribeiro, Andr\'e Coelho, Rui Campos
https://arxiv.org/abs/2506.04404

A Framework Leveraging Large Language Models for Autonomous UAV Control in Flying Networks
This paper proposes FLUC, a modular framework that integrates open-source Large Language Models (LLMs) with Unmanned Aerial Vehicle (UAV) autopilot systems to enable autonomous control in Flying Networks (FNs). FLUC translates high-level natural language commands into executable UAV mission code, bridging the gap between operator intent and UAV behaviour. FLUC is evaluated using three open-source LLMs - Qwen 2.5, Gemma 2, and LLaMA 3.2 - across scenarios involving code generation and mission …