In-Group Bias in Deep Learning-Based Face Recognition Models Due to Ethnicity and Age-Reference-Cited by-同舟云学术

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In-Group Bias in Deep Learning-Based Face Recognition Models Due to Ethnicity and Age

Published:2023-03 Issue:1 Volume:4 Page:54-67
ISSN:2637-6415
Container-title:IEEE Transactions on Technology and Society
language:
Short-container-title:IEEE Trans. Technol. Soc.

Author:

Nagpal Shruti¹^ORCID,Singh Maneet¹,Singh Richa²^ORCID,Vatsa Mayank²^ORCID,Ratha Nalini K.³^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Indraprastha Institute of Information Technology Delhi, New Delhi, India

2. Department of Computer Science and Engineering, Indian Institute of Technology Jodhpur, Jodhpur, India

3. Department of Computer Science and Engineering, University at Buffalo, Buffalo, NY, USA

Funder

the Tata Consultancy Services (TCS) Ph.D. Fellowship

Swarnajayanti Fellowship by the Government of India

the Facebook’s Ethics in AI Award

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Medicine

Link

http://xplorestaging.ieee.org/ielx7/8566059/10086685/10032592.pdf?arnumber=10032592

Reference69 articles.

1. Demographic effects on estimates of automatic face recognition performance

2. In-group gender bias in hiring: Real-world evidence

3. Accuracy Comparison Across Face Recognition Algorithms: Where Are We on Measuring Race Bias?

4. An Investigation of the Contact Hypothesis of the Own-race Bias in Face Recognition

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1. Analyzing the Impact of Demographic and Operational Variables on 1-to-Many Face ID Search;IEEE Transactions on Technology and Society;2024-06

2. A Comprehensive Review of Bias in Deep Learning Models: Methods, Impacts, and Future Directions;Archives of Computational Methods in Engineering;2024-05-08

3. Hue-Tiful Privacy: Impact of Color Correction on Privacy Preserving Techniques;SoutheastCon 2024;2024-03-15

4. Who Wore It Best? And Who Paid Less? Effects of Privacy-Preserving Techniques Across Demographics;2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW);2024-01-01

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