On bias and fairness in deep learning-based facial analysis-Reference-Cited by-同舟云学术

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On bias and fairness in deep learning-based facial analysis

Published:2023 Issue: Volume: Page:169-221
ISSN:0169-7161
Container-title:Handbook of Statistics
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Author:

Mittal Surbhi,Majumdar Puspita,Vatsa Mayank,Singh Richa

Publisher

Elsevier

Reference204 articles.

1. Measuring the gender and ethnicity bias in deep models for face recognition;Acien,2018

2. Representation learning with statistical independence to mitigate bias;Adeli,2021

3. Does data repair lead to fair models? curating contextually fair data to reduce model bias;Agarwal,2022

4. Toward fairness in face matching algorithms;Alasadi,2019

5. Is face recognition sexist? no, gendered hairstyles and biology are;Albiero,2020

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1. Bias Detection and Correction Methods for Machine Learning Algorithms;2024 5th International Conference in Electronic Engineering, Information Technology & Education (EEITE);2024-05-29

2. A Personalized Contactless Emergency Aid System Designed for Individuals With Profound Physical Disabilities;IEEE Access;2024

3. Zero-Shot Racially Balanced Dataset Generation using an Existing Biased StyleGAN2;2023 IEEE International Joint Conference on Biometrics (IJCB);2023-09-25

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