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DetoxAI: A Python Toolkit for Debiasing Deep Learning Models in Computer Vision

delete2026-01-01
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PRE
AI
I
Ignacy Stępka
L
Lukasz Sztukiewicz
M
M. Wilinski
J
Jerzy Stefanowski *
DOI:10.1007/978-3-032-06129-4_39delete
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Abstract

Abstract

En 中文
While machine learning fairness has made significant progress in recent years, most existing solutions focus on tabular data and are poorly suited for vision-based classification tasks, which rely heavily on deep learning. To bridge this gap, we introduce DetoxAI, an open-source Python library for improving fairness in deep learning vision classifiers through post-hoc debiasing. DetoxAI implements state-of-the-art debiasing algorithms, fairness metrics, and visualization tools. It supports debiasing via interventions in internal representations and includes attribution-based visualization tools and quantitative algorithmic fairness metrics to show how bias is mitigated. This paper presents the motivation, design, and use cases of DetoxAI, demonstrating its tangible value to engineers and researchers.
Keywords:
Fairness
Deep Learning
Computer Vision
Debiasing

Journal

M
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. APPLIED DATA SCIENCE TRACK AND DEMO TRACK, ECML PKDD 2025, PT X
IF:
0
Papers:
40
Citations:
0

Organization

P
poznan university of technology
Scholars:
664
Papers: 310
Citations: 0
Cited Papers

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