Anguelos Nicolaou - Pattern Recognition Lab

Angelos Nikolaou

Researcher

Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)

Room 04.159
Martensstr. 3
91058 Erlangen
Germany

Phone number: +49 9131 85-20281
Fax number: +49 9131 85-27270
Email: anguelos.nikolaou@fau.de
Website: http://www5.cs.fau.de/~nicolaou

Office hours

Due to Covid I will not be accepting people in my office. I am available for zoom or upon apointment meeting in an open space.

Each week Fr, 13:00 - 14:00,

Academic CV

Since 6/2018:
Researcher at the LME Lab
Since 10/2014:
Student (PhD) at the Computer Vision Center in Barcelona
Since 10/2010:
Student (MSc) at the University of Bern.

Projects

No projects found.

Publications

2019

Conference Contributions

Christlein V., Spranger L., Seuret M., Nikolaou A., Král P., Maier A.:
Deep Generalized Max Pooling
2019 International Conference on Document Analysis and Recognition (ICDAR) (Sydney, September 20, 2019 - September 25, 2019)
In: 2019 International Conference on Document Analysis and Recognition (ICDAR) 2019
DOI: 10.1109/ICDAR.2019.00177
URL: https://arxiv.org/abs/1908.05040
BibTeX: Download
Martínek J., Lenc L., Král P., Nikolaou A., Christlein V.:
Hybrid Training Data for Historical Text OCR
2019 International Conference on Document Analysis and Recognition (ICDAR) (Sydney, September 20, 2019 - September 25, 2019)
In: 2019 International Conference on Document Analysis and Recognition (ICDAR) 2019
DOI: 10.1109/ICDAR.2019.00096
URL: https://www.researchgate.net/profile/Vincent_Christlein/publication/339025333_Hybrid_Training_Data_for_Historical_Text_OCR/links/5e41bf48a6fdccd9659a17e2/Hybrid-Training-Data-for-Historical-Text-OCR.pdf
BibTeX: Download
Christlein V., Nikolaou A., Seuret M., Stutzmann D., Maier A.:
ICDAR 2019 Competition on Image Retrieval for Historical Handwritten Documents
2019 International Conference on Document Analysis and Recognition (ICDAR) (Sydney, September 20, 2019 - September 25, 2019)
In: 2019 International Conference on Document Analysis and Recognition (ICDAR) 2019
DOI: 10.1109/ICDAR.2019.00242
URL: https://arxiv.org/abs/1912.03713
BibTeX: Download

Lectures

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