Tootfinder

Fine-Grained Customized Fashion Design with Image-into-Prompt benchmark and dataset from LMM
Hui Li, Yi You, Qiqi Chen, Bingfeng Zhang, George Q. Huang
https://arxiv.org/abs/2509.09324

Fine-Grained Customized Fashion Design with Image-into-Prompt benchmark and dataset from LMM
Generative AI evolves the execution of complex workflows in industry, where the large multimodal model empowers fashion design in the garment industry. Current generation AI models magically transform brainstorming into fancy designs easily, but the fine-grained customization still suffers from text uncertainty without professional background knowledge from end-users. Thus, we propose the Better Understanding Generation (BUG) workflow with LMM to automatically create and fine-grain customize th…

A Certifiable Machine Learning-Based Pipeline to Predict Fatigue Life of Aircraft Structures
\'Angel Ladr\'on, Miguel S\'anchez-Dom\'inguez, Javier Rozal\'en, Fernando R. S\'anchez, Javier de Vicente, Lucas Lacasa, Eusebio Valero, Gonzalo Rubio
https://arxiv.org/abs/2509.10227…

A Certifiable Machine Learning-Based Pipeline to Predict Fatigue Life of Aircraft Structures
Fatigue life prediction is essential in both the design and operational phases of any aircraft, and in this sense safety in the aerospace industry requires early detection of fatigue cracks to prevent in-flight failures. Robust and precise fatigue life predictors are thus essential to ensure safety. Traditional engineering methods, while reliable, are time consuming and involve complex workflows, including steps such as conducting several Finite Element Method (FEM) simulations, deriving the ex…

Phoenix: A Novel Context-Aware Voice-Powered Math Equation Workspace and Editor
Kenneth Ge, Ryan Paul, Priscilla Zhang, JooYoung Seo
https://arxiv.org/abs/2508.07576 https://

Phoenix: A Novel Context-Aware Voice-Powered Math Equation Workspace and Editor
Writing mathematical notation requires substantial effort, diverting cognitive resources from conceptual understanding to documentation mechanics, significantly impacting individuals with fine motor disabilities (FMDs). Current limits of speech-based math technologies rely on precise dictation of math symbols and unintuitive command-based interfaces. We present a novel voice-powered math workspace, applying neuroscience insights to create an intuitive problem-solving environment. To minimize co…

In case you missed it: This September will be … smashing! 😻💚
@… is coming back to Freiburg on September 8–11, and I’m thrilled and honoured (and a bit baffled) to be part of this incredible lineup! Get your tickets, friends! 🔥😁

Matthias Ott — Freiburg in Germany, September 8–11.
Matthias is an independent user experience designer and web design engineer. He teaches interface prototyping at Muthesius University of Fine Arts and Design and runs workshops on modern web design, design engineering, and prototyping. He writes Own Your Web, a newsletter about personal websites, and blogs about design, development, CSS, the open web, and more on matthiasott.com.

This might be a slightly odd request but this is the fediverse after all…
Does anyone have a sextant I can borrow?
I want to have some navigation-related activities for a workshop later in the month and this would be fun.

We’ve just dropped the first draft agenda for @… ! The conference is taking place over 4 days (from Tuesday 21st October 2025 until the 24th October 2025)
This year’s edition is going to be wild, expect mind-blowing talks, hands-on workshops, extra CTF challenges during the conference, and plenty of fun activities.
Check it out and start planning yo…

Machine learning magnetism from simple global descriptors
Ahmed E. Fahmy
https://arxiv.org/abs/2509.05909 https://arxiv.org/pdf/2509.05909

Machine learning magnetism from simple global descriptors
The reliable identification of magnetic ground states remains a major challenge in high-throughput materials databases, where density functional theory (DFT) workflows often converge to ferromagnetic (FM) solutions. Here, we partially address this challenge by developing machine learning classifiers trained on experimentally validated MAGNDATA magnetic materials leveraging a limited number of simple compositional, structural, and electronic descriptors sourced from the Materials Project databas…

This might be a slightly odd request but this is the fediverse after all…
Does anyone have a sextant I can borrow?
I want to have some navigation-related activities for a workshop later in the month and this would be fun.

Like just about everyone else I know, I seem to spend a lot of time thinking, reading, and talking about #AI. And, given that I work in fine arts education, it's inevitable I think about how AI affects the arts, and how the arts affect AI.
As part of my work in #ArtsPedagogy, I'm visi…

A Multi-Stage Fine-Tuning and Ensembling Strategy for Pancreatic Tumor Segmentation in Diagnostic and Therapeutic MRI
Omer Faruk Durugol, Maximilian Rokuss, Yannick Kirchhoff, Klaus H. Maier-Hein
https://arxiv.org/abs/2508.21775

A Multi-Stage Fine-Tuning and Ensembling Strategy for Pancreatic Tumor Segmentation in Diagnostic and Therapeutic MRI
Automated segmentation of Pancreatic Ductal Adenocarcinoma (PDAC) from MRI is critical for clinical workflows but is hindered by poor tumor-tissue contrast and a scarcity of annotated data. This paper details our submission to the PANTHER challenge, addressing both diagnostic T1-weighted (Task 1) and therapeutic T2-weighted (Task 2) segmentation. Our approach is built upon the nnU-Net framework and leverages a deep, multi-stage cascaded pre-training strategy, starting from a general anatomical …