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From the 1 of 8 linked papers with an AI index.

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8 papers

cs.CV2026

Evaluating Vision Foundation Models for Pixel and Object Classification in Microscopy

Carolin Teuber, Anwai Archit, Tobias Boothe +3

The paper evaluates several vision foundation models, including SAM variants and domain‑specific models, for pixel‑level and object‑level classification tasks in microscopy, showin…

cs.CV2026

Match: Foundation Models for Semi-supervised Learning and Domain Adaptation in EM

Marei Freitag, Olesia Korchevaia, Luca Freckmann +2

Vision foundation models have substantially advanced computer vision, enabling state-of-the-art performance in zero- and few-shot settings. They have been successfully applied to b…

cs.CV2026

CellNet -- Localizing Cells using Sparse and Noisy Point Annotations

Benjamin Eckhardt, Dmytro Fishman, Stuart Fawke +3

Counting living cells is an important step in many biological research workflows. Our collaborators at the Wellcome Sanger Institute study vital genes in humans via large scale sat…

cs.CV2026

Revisiting foundation models for cell instance segmentation

Anwai Archit, Constantin Pape

Cell segmentation is a fundamental task in microscopy image analysis. Several foundation models for cell segmentation have been introduced, virtually all of them are extensions of…

eess.IV2025

BioimageAIpub: a toolbox for AI-ready bioimaging data publishing

Stefan Dvoretskii, Anwai Archit, Constantin Pape +2

Modern bioimage analysis approaches are data hungry, making it necessary for researchers to scavenge data beyond those collected within their (bio)imaging facilities. In addition t…

eess.IV2025

MedicoSAM: Robust Improvement of SAM for Medical Imaging

Anwai Archit, Luca Freckmann, Constantin Pape

Medical image segmentation is an important analysis task in clinical practice and research. Deep learning has massively advanced the field, but current approaches are mostly based…