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Zero-shot learning — Wikipedia (en)

Source: Wikipedia (en)
Original: https://en.wikipedia.org/wiki/Zero-shot_learning
License (as archived): CC-BY-SA-4.0
Archived: 2026-10-05T23:52:24.822Z
SHA-256 of the archived text: 84b49ccd55960df4986974874ce74f4471c7d2445ea0e878179cd51745fb7647
Stable URL of this page: https://metraipolis.com/documento/dc_46bbcffe20c5

How to cite

Zero-shot learning — Wikipedia (en) — Wikipedia (en), https://en.wikipedia.org/wiki/Zero-shot_learning (CC-BY-SA-4.0); archived copy: https://metraipolis.com/documento/dc_46bbcffe20c5 (Metraipolis archive dc_46bbcffe20c5, sha256 84b49ccd55960df4986974874ce74f4471c7d2445ea0e878179cd51745fb7647)

BibTeX

@misc{dc46bbcffe20c5,
  title = {Zero-shot learning — Wikipedia (en)},
  howpublished = {Wikipedia (en)},
  url = {https://en.wikipedia.org/wiki/Zero-shot_learning},
  note = {License CC-BY-SA-4.0; archived copy https://metraipolis.com/documento/dc_46bbcffe20c5; sha256 84b49ccd55960df4986974874ce74f4471c7d2445ea0e878179cd51745fb7647},
  year = {2026}
}

Archived text

Reproduced under CC-BY-SA-4.0. Attribution: Wikipedia (en), https://en.wikipedia.org/wiki/Zero-shot_learning. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Zero-shot learning (ZSL) is a problem setup in machine learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict their class. The name is a play on words based on the earlier concept of one-shot learning in computer vision, in which classification can be learned from only one example. Zero-shot methods generally work by associating observed and non-observed classes through auxiliary information that encodes observable distinguishing properties of objects. For example, given a set of images of animals to be classified, along with auxiliary textual descriptions of what animals look like, a model which has been trained to recognize horses, but has never been given a zebra, can still recognize a zebra when it also knows that zebras look like striped horses. This problem is widely studied in computer vision, natural language processing, and machine perception.

Tema degli esploratori: agenti e intelligenza artificiale (deposito sistematico; ricerca «reinforcement learning»).
Fonte: Wikipedia in inglese, voce «Zero-shot learning» — https://en.wikipedia.org/wiki/Zero-shot_learning
Wikidata Q96416030 (dati Wikidata in CC0 1.0) — https://www.wikidata.org/wiki/Q96416030
Autori: i contributori di Wikipedia (cronologia: https://en.wikipedia.org/wiki/Zero-shot_learning?action=history).
Licenza: Creative Commons Attribuzione-Condividi allo stesso modo 4.0 (CC BY-SA 4.0) — https://creativecommons.org/licenses/by-sa/4.0/. Il riuso richiede attribuzione e stessa licenza.
Estratto dell'introduzione non modificato nel contenuto; revisione 1378219950, consultata il 2026-10-05T23:21:46.360Z tramite l'API ufficiale di Wikipedia. Impronta SHA-256 dell'estratto: dc94d2e7ba9ca2ff8fd834277aaaefff66fd27af50d00707e08bb96c180a7799