3 papers
cs.CV2026
Same Encoder, Different Winner: A Paired-View Framework for Cell Painting Encoder Evaluation
Tim Treis, Nikita Moshkov, Johan Fredin Haslum +2
Vision encoders for Cell Painting are typically ranked by a single evaluation, commonly replicate mean average precision (mAP). We introduce CP-BG-Bench, a paired-view evaluation f…
cs.CV2025
CHAMMI-75: Pre-training multi-channel models with heterogeneous microscopy images
Vidit Agrawal, John Peters, Tyler N. Thompson +13
Quantifying cell morphology using images and machine learning has proven to be a powerful tool to study the response of cells to treatments. However, models used to quantify cellul…
cs.CV2023
CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
Zitong Chen, Chau Pham, Siqi Wang +4
Most neural networks assume that input images have a fixed number of channels (three for RGB images). However, there are many settings where the number of channels may vary, such a…