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Andreas Maier (1980-)

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Name	Andreas Maier
Time	1980- (Date of birth and death)
Place	Erlangen (Geburtsort) Erlangen (Wirkungsort) Deutschland
Gender	männlich
Academic degree	Prof. Dr.-Ing.
Profession	Informatiker (characteristic profession)
Related	Friedrich-Alexander-Universität Erlangen-Nürnberg Friedrich-Alexander-Universität Erlangen-Nürnberg. Department Informatik Stanford University (2009-2010) Mustererkennung (Thema) Informatik (Studienfach)
Further information	Studium der Informatik, -2005, Promotion -2009 an der Friedrich-Alexander-Universität Erlangen-Nürnberg - dort seit 2015 Leiter des Lehrstuhl für Informatik 5 (Mustererkennung)
Source	Homepage: https://www5.cs.fau.de/de/mitarbeiter/maier-andreas/lebenslauf/ (Stand: 22.07.2016)
Record type	Person
GND-Identifier	138422893
Record ID	138422893
Involved in show all Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026 Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026 A robust sampling technique for realistic distribution simulation in federated learning Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models Nuremberg Letterbooks: A Multi-Transcriptional Dataset of Early 15th Century Manuscripts for Document Analysis Lightweight cross-attention-based HookNet for historical handwritten document layout analysis Deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data Data-efficient handwritten text recognition of diplomatic historical text A robust sampling technique for realistic distribution simulation in federated learning Bildverarbeitung für die Medizin 2025 : proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 Bildverarbeitung für die Medizin 2025 : Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025 Data-efficient handwritten text recognition of diplomatic historical text Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models A deep learning approach to real-time Markov modeling of ion channel gating Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features Addressing challenges in speaker anonymization to maintain utility while ensuring privacy of pathological speech An interactive task-based method for the avoidance of metal artifacts in CBCT OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods Bildverarbeitung für die Medizin 2024 : proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 Bildverarbeitung für die Medizin 2024 : Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024 Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm Kritischer Katalog der Luther-Bildnisse (1519-1530) Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor Bildverarbeitung für die Medizin 2022 : proceedings, German workshop on medical image computing, Heidelberg, June 26-28, 2022 Bildverarbeitung für die Medizin 2022 : Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022 Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region Deep Learning-based quantification of pulmonary hemosiderophages in cytology slides Field of Interest Proposal for Augmented Mitotic Cell Count : Comparison of Two Convolutional Networks Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Microscopy Motion Artifact Detection in Confocal Laser Endomicroscopy Images Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images : A Cross-Site Robustness Assessment Probe-based confocal laser endomicroscopy in detecting malignant lesions of vocal folds Systematic interpretation of confocal laser endomicroscopy: larynx and pharynx confocal imaging score Systematic interpretation of confocal laser endomicroscopy: larynx and pharynx confocal imaging score Validation of a classification and scoring system for the diagnosis of laryngeal and pharyngeal squamous cell carcinomas by confocal laser endomicroscopy Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma Segmentation of photovoltaic module cells in uncalibrated electroluminescence images “Keep it simple, scholar”: an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning Segmentation of photovoltaic module cells in uncalibrated electroluminescence images A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research Bildverarbeitung für die Medizin 2020 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin Bildverarbeitung für die Medizin 2020 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

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Katalog der Deutschen Nationalbibliothek

Andreas Maier (1980-)

Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026

Bildverarbeitung für die Medizin 2026 : Proceedings, German Conference on Medical Image Computing, Lübeck March 15 - 17, 2026

A robust sampling technique for realistic distribution simulation in federated learning

Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models

Nuremberg Letterbooks: A Multi-Transcriptional Dataset of Early 15th Century Manuscripts for Document Analysis

Lightweight cross-attention-based HookNet for historical handwritten document layout analysis

Deep learning-based image analysis in muscle histopathology using photo-realistic synthetic data

Data-efficient handwritten text recognition of diplomatic historical text

A robust sampling technique for realistic distribution simulation in federated learning

Bildverarbeitung für die Medizin 2025 : proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025

Bildverarbeitung für die Medizin 2025 : Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025

Data-efficient handwritten text recognition of diplomatic historical text

Medical Image Computing and Computer Assisted Intervention – MICCAI 2024 Workshops : LDTM 2024, MMMI/ML4MHD 2024, ML-CDS 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6–10, 2024, Proceedings

Zero-Shot Paragraph-level Handwriting Imitation with Latent Diffusion Models

A deep learning approach to real-time Markov modeling of ion channel gating

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features

Addressing challenges in speaker anonymization to maintain utility while ensuring privacy of pathological speech

An interactive task-based method for the avoidance of metal artifacts in CBCT

OCTDL: Optical Coherence Tomography Dataset for Image-Based Deep Learning Methods

Bildverarbeitung für die Medizin 2024 : proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024

Bildverarbeitung für die Medizin 2024 : Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024

Graph neural networks in multi-stained pathological imaging: extended comparative analysis of Radiomic features

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images

Cytologic scoring of equine exercise-induced pulmonary hemorrhage: Performance of human experts and a deep learning-based algorithm

Kritischer Katalog der Luther-Bildnisse (1519-1530)

Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry

Pan-tumor T-lymphocyte detection using deep neural networks: Recommendations for transfer learning in immunohistochemistry

Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset

Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research

A large-scale dataset for mitotic figure assessment on whole slide images of canine cutaneous mast cell tumor

Bildverarbeitung für die Medizin 2022 : proceedings, German workshop on medical image computing, Heidelberg, June 26-28, 2022

Bildverarbeitung für die Medizin 2022 : Proceedings, German Workshop on Medical Image Computing, Heidelberg, June 26-28, 2022

Computer-assisted mitotic count using a deep learning–based algorithm improves interobserver reproducibility and accuracy

Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region

Deep Learning-based quantification of pulmonary hemosiderophages in cytology slides

Field of Interest Proposal for Augmented Mitotic Cell Count : Comparison of Two Convolutional Networks

Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Microscopy

Motion Artifact Detection in Confocal Laser Endomicroscopy Images

Pan-tumor CAnine cuTaneous Cancer Histology (CATCH) dataset

Patch-based Carcinoma Detection on Confocal Laser Endomicroscopy Images : A Cross-Site Robustness Assessment

Probe-based confocal laser endomicroscopy in detecting malignant lesions of vocal folds

Systematic interpretation of confocal laser endomicroscopy: larynx and pharynx confocal imaging score

Systematic interpretation of confocal laser endomicroscopy: larynx and pharynx confocal imaging score

Validation of a classification and scoring system for the diagnosis of laryngeal and pharyngeal squamous cell carcinomas by confocal laser endomicroscopy

Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Validity of tissue homogeneity in confocal laser endomicroscopy on the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Impact of intraepithelial capillary loops and atypical vessels in confocal laser endomicroscopy for the diagnosis of laryngeal and hypopharyngeal squamous cell carcinoma

Segmentation of photovoltaic module cells in uncalibrated electroluminescence images

“Keep it simple, scholar”: an experimental analysis of few-parameter segmentation networks for retinal vessels in fundus imaging

Automatic classification of cancerous tissue in laserendomicroscopy images of the oral cavity using deep learning

Segmentation of photovoltaic module cells in uncalibrated electroluminescence images

A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research

Bildverarbeitung für die Medizin 2020 : Algorithmen - Systeme - Anwendungen : Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin

Bildverarbeitung für die Medizin 2020 : Algorithmen – Systeme – Anwendungen. Proceedings des Workshops vom 15. bis 17. März 2020 in Berlin

Deep learning algorithms out-perform veterinary pathologists in detecting the mitotically most active tumor region