Foundation Models and Fine-Tuning: A Benchmark for Out of Distribution Detection-Reference-Cited by-同舟云学术

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Foundation Models and Fine-Tuning: A Benchmark for Out of Distribution Detection

Published:2024 Issue: Volume:12 Page:79401-79414
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Cappio Borlino Francesco¹^ORCID,Lu Lorenzo¹^ORCID,Tommasi Tatiana¹^ORCID

Affiliation:

1. Dipartimento di Automatica e Informatica (DAUIN), Politecnico di Torino, Turin, Italy

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6287639/10380310/10547247.pdf?arnumber=10547247

Reference53 articles.

1. A baseline for detecting misclassified and out-of-distribution examples in neural networks;Hendrycks

2. Enhancing the reliability of out-of-distribution image detection in neural networks;Liang

3. Energy-based out-of-distribution detection;Liu

4. Extremely simple activation shaping for out-of-distribution detection;Djurisic

5. DINOV2: Learning robust visual features without supervision;Oquab;Trans. Mach. Learn. Res.,2024

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