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Peter Zegelaar - IEEE Xplore Author Profile

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Author details

Peter Zegelaar

Publications

1

Citations

0

Publications by Year

20252025

Co-Authors:

Henk NijmeijerWouter ScholteTom van der Sande

Peter Zegelaar

Affiliation

Mechanical Engineering Department

Eindhoven University of Technology

Eindhoven, The Netherlands

Research and Advanced Engineering Europe

Ford Motor Company

Aachen, Germany

Publication Topics

Acceleration Profile,
Actuator,
Automated Vehicles,
Constant Velocity,
Control Performance,
Control Strategy,
Cooperative Control,
Error Dynamics,
Global Navigation Satellite System,
Kalman Filter,
Lane Change,
Low Velocity

Biography

Peter Zegelaar is a Technical Expert Driver Assistance Functions with the Ford Research and Development Center, Cologne, Germany. He was active in the field of collision avoidance: automated braking and automated steering to avoid collisions. He is currently working on highly automated driving and cooperative driving. From 2015 to 2023 he was a Part-Time Professor ’‘Smart Vehicle Technology” with the Eindhoven University of Technology, The Netherlands.(Based on document published on 17 February 2025).

Publications

1

Citations

0

Publications by Year

20252025

Co-Authors:

Henk Nijmeijer
Wouter Scholte
Tom van der Sande

Author's Published Works

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Showing 1-3 of 3 results

Conferences (2)

Early Access Articles (1)

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Sushrut Patwardhan(3)
Raghavendra Ramachandra(3)
Qing Zhao(1)
Aman Urumbekov(1)
Chao Zhou(1)
AiBA AS, Gjovik, Norway(1)
Norwegian University of Science and Technology (NTNU), Gjøvik, Norway(1)
Faculty of Computer and Information Science, University of Ljubljana, Ljubljana, Slovenia(1)
School of Physical and Applied Sciences, Goa University, Goa, India(1)
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany(1)
2024 IEEE International Joint Conference on Biometrics (IJCB)(1)
2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)(1)
IEEE Transactions on Biometrics, Behavior, and Identity Science(1)
IEEE(3)
Buffalo, NY, USA(1)
Seattle, WA, USA(1)
Data Augmentation(2)
Adam Optimizer(1)
Attention Block(1)
Attention Mechanism(1)
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PCGattnNet: A 3D Point Cloud Dynamic Graph Attention for Generalizable Face Presentation Attack Detection

Raghavendra Ramachandra;Narayan Vetrekar;Sushrut Patwardhan;Sushma Venkatesh;Gauresh Naik;R. S. Gad

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2025 | Early Access Article |

Face recognition systems that are commonly used in access control settings are vulnerable to presentation attacks, which pose a significant security risk. Therefore, it is crucial to develop a robust and reliable face presentation attack detection system that can automatically detect these types of attacks. In this paper, we present a novel technique called Point Cloud Graph Attention Network (PCG...Show More

PCGattnNet: A 3D Point Cloud Dynamic Graph Attention for Generalizable Face Presentation Attack Detection

Raghavendra Ramachandra;Narayan Vetrekar;Sushrut Patwardhan;Sushma Venkatesh;Gauresh Naik;R. S. Gad

IEEE Transactions on Biometrics, Behavior, and Identity Science

Year: 2025 | Early Access Article |

First Competition on Presentation Attack Detection on ID Card

Juan E. Tapia;Naser Damer;Christoph Busch;Juan M. Espin;Javier Barrachina;Alvaro S. Rocamora;Krištof Ocvirk;Leon Alessio;Borut Batagelj;Sushrut Patwardhan;Raghavendra Ramachandra;Raghavendra Mudgalgundurao;Kiran Raja;Daniel Schulz;Carlos Aravena

2024 IEEE International Joint Conference on Biometrics (IJCB)

Year: 2024 | Conference Paper |

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This paper summarises the Competition on Presentation Attack Detection on ID Cards (PAD-IDCard) held at the 2024 International Joint Conference on Biometrics (IJCB 2024). The competition attracted a total of ten registered teams, both from academia and industry. In the end, the participating teams submitted five valid submissions, with eight models to be evaluated by the organisers. The competitio...Show More

First Competition on Presentation Attack Detection on ID Card

Juan E. Tapia;Naser Damer;Christoph Busch;Juan M. Espin;Javier Barrachina;Alvaro S. Rocamora;Krištof Ocvirk;Leon Alessio;Borut Batagelj;Sushrut Patwardhan;Raghavendra Ramachandra;Raghavendra Mudgalgundurao;Kiran Raja;Daniel Schulz;Carlos Aravena

2024 IEEE International Joint Conference on Biometrics (IJCB)

Year: 2024 | Conference Paper |

NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results

Zheng Chen;Zongwei Wu;Eduard Zamfir;Kai Zhang;Yulun Zhang;Radu Timofte;Xiaokang Yang;Hongyuan Yu;Cheng Wan;Yuxin Hong;Zhijuan Huang;Yajun Zou;Yuan Huang;Jiamin Lin;Bingnan Han;Xianyu Guan;Yongsheng Yu;Daoan Zhang;Xuanwu Yin;Kunlong Zuo;Jinhua Hao;Kai Zhao;Kun Yuan;Ming Sun;Chao Zhou;Hongyu An;Xinfeng Zhang;Zhiyuan Song;Ziyue Dong;Qing Zhao;Xiaogang Xu;Pengxu Wei;Zhi-chao Dou;Gui-ling Wang;Chih-Chung Hsu;Chia-Ming Lee;Yi-Shiuan Chou;Cansu Korkmaz;A. Murat Tekalp;Yubin Wei;Xiaole Yan;Binren Li;Haonan Chen;Siqi Zhang;Sihan Chen;Amogh Joshi;Nikhil Akalwadi;Sampada Malagi;Palani Yashaswini;Chaitra Desai;Ramesh Ashok Tabib;Ujwala Patil;Uma Mudenagudi;Anjali Sarvaiya;Pooja Choksy;Jagrit Joshi;Shubh Kawa;Kishor Upla;Sushrut Patwardhan;Raghavendra Ramachandra;Sadat Hossain;Geongi Park;S. M. Nadim Uddin;Hao Xu;Yanhui Guo;Aman Urumbekov;Xingzhuo Yan;Wei Hao;Minghan Fu;Isaac Orais;Samuel Smith;Ying Liu;Wangwang Jia;Qisheng Xu;Kele Xu;Weijun Yuan;Zhan Li;Wenqin Kuang;Ruijin Guan;Ruting Deng;Zhao Zhang;Bo Wang;Suiyi Zhao;Yan Luo;Yanyan Wei;Asif Hussain Khan;Christian Micheloni;Niki Martinel

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2024 | Conference Paper |

Cited by: Papers (18)

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This paper reviews the NTIRE 2024 challenge on image super-resolution (×4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating corresponding high-resolution (HR) images, magnified by a factor of four, from low-resolution (LR) inputs using prior information. The LR images originate from bicubic downsampling degradation. The aim of the challenge is to ob...Show More

NTIRE 2024 Challenge on Image Super-Resolution (×4): Methods and Results

Zheng Chen;Zongwei Wu;Eduard Zamfir;Kai Zhang;Yulun Zhang;Radu Timofte;Xiaokang Yang;Hongyuan Yu;Cheng Wan;Yuxin Hong;Zhijuan Huang;Yajun Zou;Yuan Huang;Jiamin Lin;Bingnan Han;Xianyu Guan;Yongsheng Yu;Daoan Zhang;Xuanwu Yin;Kunlong Zuo;Jinhua Hao;Kai Zhao;Kun Yuan;Ming Sun;Chao Zhou;Hongyu An;Xinfeng Zhang;Zhiyuan Song;Ziyue Dong;Qing Zhao;Xiaogang Xu;Pengxu Wei;Zhi-chao Dou;Gui-ling Wang;Chih-Chung Hsu;Chia-Ming Lee;Yi-Shiuan Chou;Cansu Korkmaz;A. Murat Tekalp;Yubin Wei;Xiaole Yan;Binren Li;Haonan Chen;Siqi Zhang;Sihan Chen;Amogh Joshi;Nikhil Akalwadi;Sampada Malagi;Palani Yashaswini;Chaitra Desai;Ramesh Ashok Tabib;Ujwala Patil;Uma Mudenagudi;Anjali Sarvaiya;Pooja Choksy;Jagrit Joshi;Shubh Kawa;Kishor Upla;Sushrut Patwardhan;Raghavendra Ramachandra;Sadat Hossain;Geongi Park;S. M. Nadim Uddin;Hao Xu;Yanhui Guo;Aman Urumbekov;Xingzhuo Yan;Wei Hao;Minghan Fu;Isaac Orais;Samuel Smith;Ying Liu;Wangwang Jia;Qisheng Xu;Kele Xu;Weijun Yuan;Zhan Li;Wenqin Kuang;Ruijin Guan;Ruting Deng;Zhao Zhang;Bo Wang;Suiyi Zhao;Yan Luo;Yanyan Wei;Asif Hussain Khan;Christian Micheloni;Niki Martinel

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Year: 2024 | Conference Paper |

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