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Found 7 papers, 1 papers with code
Noise contrastive estimation with soft targets for conditional models
Our new soft target InfoNCE loss is conceptually simple, efficient to compute, and can be derived within the framework of noise contrastive estimation.
MIFA: Metadata, Incentives, Formats, and Accessibility guidelines to improve the reuse of AI datasets for bioimage analysis
These include standards on data formats, metadata, data presentation and sharing, and incentives to generate new datasets.
Made to measure: an introduction to quantification in microscopy data
Acknowledging that what makes a measurement "good" is ultimately down to the biological question being investigated, this review aims at providing readers with a toolkit to challenge how they quantify their own data and be critical of conclusions drawn from quantitative bioimage analysis experiments.
Deep learning for bioimage analysis
Deep learning has transformed the way large and complex image datasets can be processed, reshaping what is possible in bioimage analysis.
aura-net : robust segmentation of phase-contrast microscopy images with few annotations
We present AURA-net, a convolutional neural network (CNN) for the segmentation of phase-contrast microscopy images.
Principled Design and Implementation of Steerable Detectors
We provide a complete pipeline for the detection of patterns of interest in an image.
Diverse M-Best Solutions by Dynamic Programming
Many computer vision pipelines involve dynamic programming primitives such as finding a shortest path or the minimum energy solution in a tree-shaped probabilistic graphical model.
