Paper Citation Record · LEDGER

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces

As of 9 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2505.14320.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.14320 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:41:14.428184Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:10:53.631985Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

58 of 58 outbound references displayed

verified exact3
verified fuzzy48
unresolved5
parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da9bd00d-7c2f-4a84-9e4e-048e623a5b39 · outbound

This paper cites A forensic without the science: face recognition in US criminal inves- tigations.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces A forensic without the science: face recognition in US criminal inves- tigations

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:25.949483Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bf175ca7-ae60-4c18-9024-701323ef3e85 · outbound

This paper cites Linden L, editor.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Linden L, editor

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:25.730665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 73178554-6f21-491f-b065-daf8ed417828 · outbound

This paper cites Face Recognition Vendor Test (FR VT); 2019.https:// www.nist.gov/programs-projects/face-recognition-vendor-test-frvt.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Face Recognition Vendor Test (FR VT); 2019.https:// www.nist.gov/programs-projects/face-recognition-vendor-test-frvt

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:25.581567Z

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Observation 40fa04cf-1dcc-478e-a913-407d0983c382 · outbound

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Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Unresolved cited work

Reference 4

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Observation 00397093-3b43-4361-9fbe-ca2d73562628 · outbound

This paper cites an unresolved cited work.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:41:25.174700Z

Source-reported events for the cited work

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Observation 5a9d2cc4-a738-40b0-9878-c8528cc037aa · outbound

This paper cites Learning to under- stand image blur.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Learning to under- stand image blur

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:24.961247Z

Source-reported events for the cited work

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Observation 8fe0cd96-d007-4b44-bb1c-f4aea1034bf0 · outbound

This paper cites Image partial blur detection and classification.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Image partial blur detection and classification

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:24.698692Z

Source-reported events for the cited work

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Observation 15ae50b1-fe4b-4256-ac75-2e42db8ac607 · outbound

This paper cites Face recognition across non-uniform motion blur, illumination, and pose.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Face recognition across non-uniform motion blur, illumination, and pose

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:24.519514Z

Source-reported events for the cited work

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Observation 03887636-428b-4765-b351-0b5cc630bebb · outbound

This paper cites Prioritising quality: investigating the influence of image quality on forensic facial comparison.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Prioritising quality: investigating the influence of image quality on forensic facial comparison

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:24.302775Z

Source-reported events for the cited work

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Observation afcf6973-cb6c-435e-a9c2-8b4a00880a07 · outbound

This paper cites Pixel-Level Face Image Quality Assessment for Explainable Face Recognition.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Pixel-Level Face Image Quality Assessment for Explainable Face Recognition

Reference 10

Resolution: verified exact; raw_fallback, observed 2026-08-07T15:41:15.382811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d9eda2e1-3e28-43c1-8426-054578490117 · outbound

This paper cites Face recognition vendor test (fvrt): Part 3, demographic effects.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Face recognition vendor test (fvrt): Part 3, demographic effects

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:24.157756Z

Source-reported events for the cited work

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Observation 16d9fc8c-1489-4efc-99d1-e553fb8f8fc0 · outbound

This paper cites Accuracy comparison across face recognition algorithms: Where are we on measuring race bias? IEEE transactions on biometrics, behavior, and identity science.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Accuracy comparison across face recognition algorithms: Where are we on measuring race bias? IEEE transactions on biometrics, behavior, and identity science

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:23.933791Z

Source-reported events for the cited work

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Observation 38f2a230-4796-42d3-ac17-fbb4ae310055 · outbound

This paper cites Benchmarking Algorithmic Bias in Face Recognition: An Experimental Approach Using Synthetic Faces and Human Evaluation.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Benchmarking Algorithmic Bias in Face Recognition: An Experimental Approach Using Synthetic Faces and Human Evaluation

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:23.740797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bdaa1f17-1c13-4509-b3c6-5e596c5bca51 · outbound

This paper cites Learning Face Image Qual- ity from Human Assessments.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Learning Face Image Qual- ity from Human Assessments

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:23.425063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0034835c-5f28-4e57-8d14-c0a5b97adfd1 · outbound

This paper cites The effect of broad and specific demo- graphic homogeneity on the imposter distributions and false match rates in face recognition algorithm performance.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces The effect of broad and specific demo- graphic homogeneity on the imposter distributions and false match rates in face recognition algorithm performance

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:23.092683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7e187011-2b78-4ad9-81f4-5c75a7012b1e · outbound

This paper cites Quantifying the extent to which race and gender features determine identity in commercial face recognition algorithms.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Quantifying the extent to which race and gender features determine identity in commercial face recognition algorithms

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:22.700295Z

Source-reported events for the cited work

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Observation 22fe254f-d26a-4bec-b071-537b382d8eee · outbound

This paper cites Disparate impact in facial recognition stems from the broad homogeneity effect: A case study and method to resolve.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Disparate impact in facial recognition stems from the broad homogeneity effect: A case study and method to resolve

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:22.259635Z

Source-reported events for the cited work

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Observation 1139c955-92dd-4aa2-b5b3-cbc81802b4a9 · outbound

This paper cites Evaluat- ing proposed fairness models for face recognition algorithms.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Evaluat- ing proposed fairness models for face recognition algorithms

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:21.844413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4cd25fbb-8f52-46ed-ab93-4abb9f88b48b · outbound

This paper cites Reformer TM, editor; 2025.https://minnesotareformer.com/2025/ 02/04/facial-recognition-in-policing-is-getting-state-by-state- guardrails/.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Reformer TM, editor; 2025.https://minnesotareformer.com/2025/ 02/04/facial-recognition-in-policing-is-getting-state-by-state- guardrails/

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:21.602851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation be40fe89-c6c2-45ad-841d-c12d2686a22b · outbound

This paper cites Challenging facial recognition software in criminal court.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Challenging facial recognition software in criminal court

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:21.384401Z

Source-reported events for the cited work

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Observation 34b0f147-dddc-41ec-a080-d30d47037cfa · outbound

This paper cites State of New Jersey vs.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces State of New Jersey vs

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:21.192514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d0dce72-8ef8-4bcd-a886-5fdecd3a9f00 · outbound

This paper cites NA, editor.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces NA, editor

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:21.044301Z

Source-reported events for the cited work

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Observation 103c76d4-a4aa-41a5-82ac-9fb3853c226a · outbound

This paper cites Confronting the biased algorithm: the danger of admitting fa- cial recognition technology results in the courtroom.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Confronting the biased algorithm: the danger of admitting fa- cial recognition technology results in the courtroom

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.893316Z

Source-reported events for the cited work

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Observation 1bbff289-3434-40a4-ad4b-62929290457e · outbound

This paper cites Face-to-face with facial recognition evidence: Admissibility under the post-crawford confrontation clause.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Face-to-face with facial recognition evidence: Admissibility under the post-crawford confrontation clause

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.756241Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 837e46f6-4e75-4f9d-a306-0d4c56cc11b9 · outbound

This paper cites NA, editor.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces NA, editor

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.614470Z

Source-reported events for the cited work

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Observation cd326171-fbf2-4147-92fd-0bdbc4ae48d6 · outbound

This paper cites Reliability and Validity of Forensic Science Evidence.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Reliability and Validity of Forensic Science Evidence

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.464997Z

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Observation 81cb95c6-96e0-48b2-80f8-bb396191abbc · outbound

This paper cites Ongoing face recognition vendor test (FR VT) part 1: Verification.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Ongoing face recognition vendor test (FR VT) part 1: Verification

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.345328Z

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Observation 172fbaf9-1254-41ae-b31f-5c2d92c31ea4 · outbound

This paper cites Accuracy and reliability of forensic latent fingerprint decisions.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Accuracy and reliability of forensic latent fingerprint decisions

Reference 28

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Observation 325b9749-6888-4fc5-bb38-a4cbc638bf44 · outbound

This paper cites A study of false-positive and false-negative error rates in cartridge case comparisons.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces A study of false-positive and false-negative error rates in cartridge case comparisons

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.215746Z

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Observation 226c54b2-be4c-47e0-990e-3b415e542f26 · outbound

This paper cites Methodological problems in every black-box study of forensic firearm comparisons.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Methodological problems in every black-box study of forensic firearm comparisons

Reference 30

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Observation 008c2f3c-4de2-486e-bc89-b017751597b6 · outbound

This paper cites FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces FRCSyn Challenge at WACV 2024:Face Recognition Challenge in the Era of Synthetic Data

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:41:15.101765Z

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Observation 3ed961bf-642c-445b-8304-5f8be039b01b · outbound

This paper cites The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognition.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces The Impact of Balancing Real and Synthetic Data on Accuracy and Fairness in Face Recognition

Reference 32

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Observation 32cbe4ea-1314-4c75-b5d8-158478b389d4 · outbound

This paper cites Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Synthetic to Authentic: Transferring Realism to 3D Face Renderings for Boosting Face Recognition

Reference 33

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Observation 76f1d7f6-1754-43b9-90e8-db147a64fc6c · outbound

This paper cites Alias- free generative adversarial networks.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Alias- free generative adversarial networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:20.093648Z

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Observation 876a8d88-1126-4ebe-a5e5-e2d8920f4df3 · outbound

This paper cites Third time’s the charm? image and video editing with stylegan3.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Third time’s the charm? image and video editing with stylegan3

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.958037Z

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Observation a6f2cf01-0f39-4ec7-b436-d9c358ae66ab · outbound

This paper cites Examining Pathological Bias in a Generative Adversarial Network Discriminator: A Case Study on a StyleGAN3 Model.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Examining Pathological Bias in a Generative Adversarial Network Discriminator: A Case Study on a StyleGAN3 Model

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.813116Z

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Observation 4dd4e3aa-41c1-44f2-8f36-374df2d2be7b · outbound

This paper cites A style-based generator architecture for generative adversarial networks.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces A style-based generator architecture for generative adversarial networks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.652509Z

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Observation 5b2f9fee-dc38-4e7f-b244-9fdd289499fa · outbound

This paper cites Exposing GAN- generated profile photos from compact embeddings.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Exposing GAN- generated profile photos from compact embeddings

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.475390Z

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Observation f5945586-6491-4c24-b237-7516f022a684 · outbound

This paper cites Studying bias in gans through the lens of race.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Studying bias in gans through the lens of race

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.267769Z

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Observation 63e5b242-38f9-4423-8fca-72b869d27eed · outbound

This paper cites MRMCsamplesize: An R Package for Esti- mating Sample Sizes for Multi-Reader Multi-Case Studies.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces MRMCsamplesize: An R Package for Esti- mating Sample Sizes for Multi-Reader Multi-Case Studies

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:19.075980Z

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Observation c9009de0-08d7-435d-a742-5a6f2c5c9214 · outbound

This paper cites Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Fairface: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:18.803407Z

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Observation edd819e5-409e-4951-b20c-74ae15a08e48 · outbound

This paper cites Gandiffface: Controllable generation of synthetic datasets for face recog- nition with realistic variations.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Gandiffface: Controllable generation of synthetic datasets for face recog- nition with realistic variations

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:18.651978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation acc8a68c-534b-4411-9723-ac50282f2b34 · outbound

This paper cites Age boundaries in juvenile justice systems.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Age boundaries in juvenile justice systems

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:18.490772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 48dafa8e-a650-48b6-9700-fcbfa8ed94a6 · outbound

This paper cites Juvenile Offenders Ordinance, Cap.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Juvenile Offenders Ordinance, Cap

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:18.340558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3804294b-b639-4817-b860-16f32590a416 · outbound

This paper cites Age of criminal responsibility; 2025.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Age of criminal responsibility; 2025

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:17.904946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 46abfd51-c636-4a02-8e61-41d86641e09d · outbound

This paper cites Minimum age of criminal responsibility; 2025.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Minimum age of criminal responsibility; 2025

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:17.666789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a4bc4ddc-2ec6-4ed5-bbd2-b75e3b8618be · outbound

This paper cites 2020 Census Redistricting Data (Public Law 94-171) Summary File; 2021.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces 2020 Census Redistricting Data (Public Law 94-171) Summary File; 2021

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:17.442966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ab68f79-3098-4e0d-b499-ce1da4fb3cc3 · outbound

This paper cites The OpenCV Library.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces The OpenCV Library

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:17.266401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a42bc623-4783-4fff-8cb6-b09ac16bdeac · outbound

This paper cites Blur-Generator: Simulates realistic blur on images using Python; 2023.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Blur-Generator: Simulates realistic blur on images using Python; 2023

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:17.112831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c9b6c92e-34f7-473d-832f-1c8d6b58b59c · outbound

This paper cites Interpreting the latent space of gans for semantic face editing.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Interpreting the latent space of gans for semantic face editing

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:16.881944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3fa48cea-e4f7-456b-974e-1d0993cad30d · outbound

This paper cites LightFace: A Hybrid Deep Face Recognition Frame- work.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces LightFace: A Hybrid Deep Face Recognition Frame- work

Reference 51

Resolution: malformed identifier; no resolver link, observed 2026-08-07T15:41:13.951417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 171004e4-4ce5-4d03-ac9a-6b90937e6f57 · outbound

This paper cites Retinaface: Single-shot multi- level face localisation in the wild.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Retinaface: Single-shot multi- level face localisation in the wild

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:16.613457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 25b07f40-3dcb-429b-a198-2af8459c5bfb · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Arcface: Additive angular margin loss for deep face recognition

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:16.390636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6fac410a-80fe-4beb-966a-7b9054cfc324 · outbound

This paper cites Face recognition oak ridge (faro): A framework for distributed and scalable biometrics applications.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Face recognition oak ridge (faro): A framework for distributed and scalable biometrics applications

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:16.223665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2f2fe7e4-e0bf-4141-bdeb-f36a69c50376 · outbound

This paper cites FR VT 1:1 Verification Visa Results; n.d.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces FR VT 1:1 Verification Visa Results; n.d

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:15.951307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bd3cf2fa-422f-476d-a485-5f60e1a12823 · outbound

This paper cites NA, editor.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces NA, editor

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:15.768053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5023b456-cc1a-4c36-b04c-e195d7febb2d · outbound

This paper cites Replicating Gimp’s brightness/contrast adjustment in python.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Replicating Gimp’s brightness/contrast adjustment in python

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:41:15.576112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 2426306f-9fd8-4aab-b90d-ee4eac787771 · outbound

This paper cites an unresolved cited work.

Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces Unresolved cited work

Reference 2022

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:41:18.110359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Pith citing papers

Observation 4d4cbcde-9061-45cc-b82a-2b5b26fc63e5 · inbound

A Lightweight Ensemble-Based Face Image Quality Assessment Method with Correlation-Aware Loss cites this paper.

A Lightweight Ensemble-Based Face Image Quality Assessment Method with Correlation-Aware Loss Accuracy and Fairness of Facial Recognition Technology in Low-Quality Police Images: An Experiment With Synthetic Faces

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T18:10:53.631985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.