Andreas Uhl mainly focuses on Artificial intelligence, Pattern recognition, Computer vision, Biometrics and Iris recognition. His Feature extraction, Wavelet transform, Image processing and Deep learning study in the realm of Artificial intelligence connects with subjects such as Colonic Polyp. His work carried out in the field of Pattern recognition brings together such families of science as Ground truth, Local binary patterns and Invariant.
The study incorporates disciplines such as Cryptography, Data mining and Fuzzy logic in addition to Biometrics. His studies in Iris recognition integrate themes in fields like IRIS, Segmentation, Key and Iris. His Wavelet study incorporates themes from Algorithm, Filter and Digital watermarking.
Artificial intelligence, Computer vision, Pattern recognition, Biometrics and Feature extraction are his primary areas of study. Iris recognition, Wavelet, Wavelet transform, Segmentation and Contextual image classification are the primary areas of interest in his Artificial intelligence study. His Wavelet research focuses on subjects like Algorithm, which are linked to Theoretical computer science.
His research on Computer vision often connects related areas such as Robustness. His Pattern recognition study incorporates themes from Local binary patterns and Image. His work carried out in the field of Biometrics brings together such families of science as Data mining and Identification.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Biometrics, Computer vision and Finger vein recognition. Artificial intelligence is a component of his Feature extraction, Iris recognition, Convolutional neural network, Segmentation and IRIS studies. His Feature extraction research is multidisciplinary, relying on both Data mining and Robustness.
Andreas Uhl studied Pattern recognition and Fingerprint recognition that intersect with Matching and Fingerprint. His Biometrics study integrates concerns from other disciplines, such as Facial recognition system, Face, Image warping, Image and Pattern recognition. His Computer vision study combines topics in areas such as Authentication, Dorsum, Scanner and Data set.
Andreas Uhl mostly deals with Artificial intelligence, Pattern recognition, Biometrics, Feature extraction and Computer vision. His Iris recognition, Finger vein recognition, Convolutional neural network, IRIS and Segmentation study are his primary interests in Artificial intelligence. His Pattern recognition research includes themes of Persistent homology, Spoofing attack, Margin, Deep learning and Perspective.
His Biometrics study combines topics from a wide range of disciplines, such as Word error rate, Image processing, Multivariate statistics, Eeg recording and Autoregressive model. His research in Feature extraction intersects with topics in Image segmentation, Data mining, Geometric shape, Rotation and Support vector machine. The Computer vision study combines topics in areas such as Dorsum and Data set.
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A survey on biometric cryptosystems and cancelable biometrics
Christian Rathgeb;Andreas Uhl.
Eurasip Journal on Information Security (2011)
Survey of wavelet-domain watermarking algorithms
Peter Meerwald;Andreas Uhl.
Proceedings of SPIE (2001)
BlenSor: blender sensor simulation toolbox
Michael Gschwandtner;Roland Kwitt;Andreas Uhl;Wolfgang Pree.
international symposium on visual computing (2011)
SELECTIVE BITPLANE ENCRYPTION FOR SECURE TRANSMISSION OF IMAGE DATA IN MOBILE ENVIRONMENTS
Martina Podesser;Hans-Peter Schmidt;Andreas Uhl.
Computer-Aided Decision Support Systems for Endoscopy in the Gastrointestinal Tract: A Review
Michael Liedlgruber;Andreas Uhl.
IEEE Reviews in Biomedical Engineering (2011)
Image and Video Encryption: From Digital Rights Management to Secured Personal Communication
Andreas Uhl;Andreas Pommer.
A Survey of H.264 AVC/SVC Encryption
T. Stutz;A. Uhl.
IEEE Transactions on Circuits and Systems for Video Technology (2012)
Weighted adaptive Hough and ellipsopolar transforms for real-time iris segmentation
Andreas Uhl;Peter Wild.
international conference on biometrics (2012)
Depreciating Motivation and Empirical Security Analysis of Chaos-Based Image and Video Encryption
Mario Preishuber;Thomas Hutter;Stefan Katzenbeisser;Andreas Uhl.
IEEE Transactions on Information Forensics and Security (2018)
Selective encryption of wavelet-packet encoded image data: efficiency and security
Andreas Pommer;Andreas Uhl.
Multimedia Systems (2003)
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