Vision foundation model features improve pixel and object classification in microscopy over hand-crafted features, and object-guided attentive probing (ObAP) can match or beat supervised baselines with very few labels.
scikit-image: Image processing in Python
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
abstract
scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal "Modified BSD" open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image.
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Evaluating Vision Foundation Models for Pixel and Object Classification in Microscopy
Vision foundation model features improve pixel and object classification in microscopy over hand-crafted features, and object-guided attentive probing (ObAP) can match or beat supervised baselines with very few labels.