Home › Entities › academia › <i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images

<i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images

Research article (Proceedings of the 32nd ACM International Conference on Multimedia, 2024) · cited 14× · AI/ML
academia openalex:W4403791669
Press Enter · cited answer in seconds

P 2 SAM: Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images

Summary

P 2 SAM: Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images is a scholarly article[1].

Key Facts

  • P 2 SAM: Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images's instance of is recorded as scholarly article[2].

References

Programmatic citations — every numbered marker resolves to a verifiable graph row below.

Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

Class ancestry

  1. [1] ↑ . Wikidata. wikidata.org.

📑 Cite this page

Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.

APA 4ort.xyz Knowledge Graph. (2026). <i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images. Retrieved May 24, 2026, from https://4ort.xyz/entity/i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images
MLA “<i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images.
BibTeX @misc{4ortxyz_i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{<i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images}}, year = {2026}, url = {https://4ort.xyz/entity/i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): <i> P <sup>2</sup> SAM: </i> Probabilistically Prompted SAMs Are Efficient Segmentator for Ambiguous Medical Images — https://4ort.xyz/entity/i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images (retrieved 2026-05-24)

Canonical URL: https://4ort.xyz/entity/i-p-sup-2-sup-sam-i-probabilistically-prompted-sams-are-efficient-segmentator-for-ambiguous-medical-images · Last refreshed: