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162
kategorie
2 032
podkategorie
23 060
pojęcia
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pojęcia

Zero-Shot Classification

Classification technique where the model infers labels for unknown classes by mapping data features to semantic descriptions of classes.

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Semantic Transfer

Process of transferring knowledge between semantic domains to generalize to unobserved classes during training.

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Semantic Spaces

Continuous vector representations where semantic concepts are projected to enable comparisons and knowledge transfers.

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Semantic Attributes

Binary or continuous descriptive characteristics that describe object properties and serve as a bridge between seen and unseen classes.

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Word Embeddings

Dense vector representations of words capturing their semantic relationships, used as prior knowledge in zero-shot learning.

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Vision-Language Models

Unified neural architectures capable of understanding and simultaneously linking visual content and textual descriptions.

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Extreme Generalization

Ability of a model to perform on data distributions radically different from those used during training.

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Learning with Limited Data

Learning scenario where labeled data is scarce or non-existent for certain target classes.

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Inference on Unknown Classes

Prediction process where the model must classify inputs into categories never encountered during training.

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Knowledge Transfer

Mechanism that allows reusing knowledge acquired on a source task to solve a different target task.

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Semantic Mapping

Mathematical function that projects visual features into a semantic space shared with textual descriptions.

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Meta-learning

Learning approach where the model learns to learn, optimizing its ability to quickly adapt to new tasks with few examples.

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Multi-modal Projection

Technique that aligns different modalities (text, image, audio) in a common vector space for knowledge transfer.

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