What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Computer vision
- Biometrics
His primary areas of investigation include Biometrics, Artificial intelligence, Data mining, Iris recognition and Feature extraction.
His Biometrics study is focused on Computer security in general.
His Computer security research incorporates themes from Emerging technologies and Benchmark.
His Artificial intelligence research incorporates themes from Computer vision and Pattern recognition.
His studies in Feature extraction integrate themes in fields like IRIS, Software engineering and Usability.
His Cryptography study incorporates themes from Homomorphic encryption, Biometric data and Internet privacy.
His most cited work include:
- A survey on biometric cryptosystems and cancelable biometrics (443 citations)
- Alignment-free cancelable iris biometric templates based on adaptive bloom filters (82 citations)
- Secure iris recognition based on local intensity variations (76 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Biometrics, Artificial intelligence, Pattern recognition, Iris recognition and Computer vision.
His work carried out in the field of Biometrics brings together such families of science as Data mining, Identification and Bloom filter.
His Data mining study combines topics from a wide range of disciplines, such as Cryptography, Fuzzy logic, Key, Error detection and correction and Search engine indexing.
His Pattern recognition research focuses on Speech recognition and how it connects with Mixture model.
The various areas that Christian Rathgeb examines in his Iris recognition study include Signature recognition, Discriminative model, Hamming distance and Similarity.
The concepts of his Feature extraction study are interwoven with issues in Algorithm and Image fusion.
He most often published in these fields:
- Biometrics (69.83%)
- Artificial intelligence (63.13%)
- Pattern recognition (37.99%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (63.13%)
- Biometrics (69.83%)
- Facial recognition system (19.55%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Biometrics, Facial recognition system, Face and Computer vision.
His research on Artificial intelligence often connects related areas such as Pattern recognition.
Christian Rathgeb performs integrative Biometrics and Quality research in his work.
His Facial recognition system research is multidisciplinary, incorporating perspectives in Spoofing attack, Word error rate, Morphing, Feature extraction and Data science.
As a member of one scientific family, Christian Rathgeb mostly works in the field of Face, focusing on Feature and, on occasion, Margin and Key.
In his research on the topic of Segmentation, Iris recognition is strongly related with Mobile device.
Between 2019 and 2021, his most popular works were:
- Demographic Bias in Biometrics: A Survey on an Emerging Challenge (48 citations)
- Deep Face Representations for Differential Morphing Attack Detection (20 citations)
- Morphing Attack Detection - Database, Evaluation Platform and Benchmarking (12 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Computer vision
- Algorithm
His primary areas of study are Facial recognition system, Artificial intelligence, Biometrics, Face and Pattern recognition.
His Facial recognition system research is multidisciplinary, incorporating elements of Spoofing attack, Morphing and Word error rate.
As part of the same scientific family, Christian Rathgeb usually focuses on Artificial intelligence, concentrating on Computer vision and intersecting with Human assessment.
His work deals with themes such as Image quality, Robustness and Data science, which intersect with Biometrics.
His Feature vector study in the realm of Pattern recognition interacts with subjects such as Differential.
His Overfitting research includes themes of Feature extraction and FERET.
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