Enhancing generalization in zero-shot multi-label endoscopic instrument classification

These findings demonstrate that sentence embeddings and z-score normalization can substantially enhance the generalization performance of zero-shot learning models. However, as the study is based on a single dataset, future work should validate the method across diverse datasets and application domains to establish its robustness and broader applicability.

Authors

Christoph Palm (ORCID: https://orcid.org/0000-0001-9468-2871)
David Rauber (ORCID: https://orcid.org/0009-0006-1782-5035)
Danilo Weber Nunes (ORCID: https://orcid.org/0000-0002-0401-0842)
Tobias Rueckert (ORCID: https://orcid.org/0009-0005-0628-1979)
Max Gutbrod
Raphaela Maerkl

Institutions

OTH Regensburg (DE)
University Hospital Regensburg (DE)
Robotic Research (United States) (US)
University of Regensburg (DE)

Publication Details

Journal: International Journal of Computer Assisted Radiology and Surgery
Published: 2025-06-11
DOI: https://doi.org/10.1007/s11548-025-03439-5
Citations: 1
Primary Topic: Colorectal Cancer Screening and Detection
Type: article
Field-Weighted Citation Impact: 1.05

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article

Enhancing generalization in zero-shot multi-label endoscopic instrument classification

Christoph Palm, David Rauber, Danilo Weber Nunes, Tobias Rueckert et al.

Jun 11, 2025

1 citations

International Journal of Computer Assisted Radiology and Surgery

Colorectal Cancer Screening and Detection

1.05

article

Enhancing generalization in zero-shot multi-label endoscopic instrument classification

Christoph Palm, David Rauber, Danilo Weber Nunes, Tobias Rueckert, Max Gutbrod, Raphaela Maerkl

June 11, 2025article en

1 citations

Abstract

These findings demonstrate that sentence embeddings and z-score normalization can substantially enhance the generalization performance of zero-shot learning models. However, as the study is based on a single dataset, future work should validate the method across diverse datasets and application domains to establish its robustness and broader applicability.

International Journal of Computer Assisted Radiology and SurgeryVol. 20(8)

OTH Regensburg (DE), University Hospital Regensburg (DE), Robotic Research (United States) (US), University of Regensburg (DE)

Openalex Percentile: Top 21%

Colorectal Cancer Screening and Detection

1.05

DOI Open Access PDF OpenAlex

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Enhancing generalization in zero-shot multi-label endoscopic instrument classification — Christoph Palm, David Rauber, et al. · International Journal of Computer Assisted Radiology and Surgery (2025) | TGRS Research Map | TGRS