Glossary Library

Technical GlossaryComputer Vision

U-Net

An encoder-decoder segmentation architecture especially effective in biomedical and pixel-level tasks.

U-Net is one of the most widely used architectures in segmentation and is especially known for producing strong results with limited data. Its encoder-decoder design and skip connections preserve both global context and fine detail. It is used in a wide range of applications from biomedical images to industrial segmentation. It remains one of the core reference points in segmentation architecture design.

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K-Means

One of the most common clustering algorithms, which partitions data points into k clusters based on distance to centroids.

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Consensus Clustering

An approach that combines multiple clustering results to obtain a more stable and reliable cluster structure.

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Cross-Attention

An attention mechanism that allows one representation set to draw context from another representation set.