Brian Pulfer

Orcid: 0000-0003-0809-6978

According to our database1, Brian Pulfer authored at least 14 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Authentication of Copy Detection Patterns: A Pattern Reliability Based Approach.
IEEE Trans. Inf. Forensics Secur., 2024

A Machine Learning-Based Digital Twin for Anti-Counterfeiting Applications With Copy Detection Patterns.
IEEE Trans. Inf. Forensics Secur., 2024

Assessing the Viability of Synthetic Physical Copy Detection Patterns on Different Imaging Systems.
CoRR, 2024

Evaluation of Security of ML-based Watermarking: Copy and Removal Attacks.
CoRR, 2024

2023
Model vs system level testing of autonomous driving systems: a replication and extension study.
Empir. Softw. Eng., June, 2023

Mind the Gap! A Study on the Transferability of Virtual Versus Physical-World Testing of Autonomous Driving Systems.
IEEE Trans. Software Eng., April, 2023

2022
Solving the Weather4cast Challenge via Visual Transformers for 3D Images.
CoRR, 2022

Mathematical model of printing-imaging channel for blind detection of fake copy detection patterns.
Proceedings of the IEEE International Workshop on Information Forensics and Security, 2022

Anomaly localization for copy detection patterns through print estimations.
Proceedings of the IEEE International Workshop on Information Forensics and Security, 2022

Printing variability of copy detection patterns.
Proceedings of the IEEE International Workshop on Information Forensics and Security, 2022

Digital twins of physical printing-imaging channel.
Proceedings of the IEEE International Workshop on Information Forensics and Security, 2022

Authentication Of Copy Detection Patterns Under Machine Learning Attacks: A Supervised Approach.
Proceedings of the 2022 IEEE International Conference on Image Processing, 2022

2021
Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driving Systems.
CoRR, 2021



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