2002 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to pattern recognition with applications to speech processing and image understanding, and for service to IAPR.
Artificial intelligence, Speech recognition, Natural language processing, Computer vision and Segmentation are his primary areas of study. Heinrich Niemann interconnects Data mining and Pattern recognition in the investigation of issues within Artificial intelligence. His Speech recognition research incorporates themes from Entropy and Statistical model.
His Natural language processing research is multidisciplinary, incorporating perspectives in Prosody and Dialog system, Dialog box. His Computer vision research focuses on Visualization and how it connects with Accumulator, Concurrent computing and Median filter. In his study, which falls under the umbrella issue of Segmentation, Sequence is strongly linked to Dialog act.
His main research concerns Artificial intelligence, Computer vision, Natural language processing, Speech recognition and Pattern recognition. His Artificial intelligence study frequently involves adjacent topics like Machine learning. His research investigates the connection with Computer vision and areas like Computer graphics which intersect with concerns in Visualization.
His Natural language processing research focuses on Dialog system and how it relates to Utterance. He regularly ties together related areas like Word in his Speech recognition studies. The study incorporates disciplines such as Motion estimation and Image in addition to Pattern recognition.
His scientific interests lie mostly in Artificial intelligence, Computer vision, Video tracking, Speech recognition and Pattern recognition. His Artificial intelligence study combines topics in areas such as Machine learning and Natural language processing. The various areas that Heinrich Niemann examines in his Natural language processing study include Speech corpus, Speech analytics and Word.
His research in Computer vision tackles topics such as Computer graphics which are related to areas like Augmented reality and Visualization. His Speech recognition research is multidisciplinary, incorporating elements of Context and Facial recognition system. In general Pattern recognition, his work in Linde–Buzo–Gray algorithm is often linked to Hand eye calibration, Data selection and Energy minimization linking many areas of study.
The scientist’s investigation covers issues in Artificial intelligence, Computer vision, Video tracking, Orientation and Robustness. His is doing research in Segmentation, Pixel, Image processing, Active contour model and Hough transform, both of which are found in Artificial intelligence. His work in Computer vision addresses issues such as Calibration, which are connected to fields such as Sequence.
His Video tracking research incorporates elements of Inverse and Feature tracking. His Orientation study combines topics from a wide range of disciplines, such as Robot and Endoscope, Surgery. His studies in Robustness integrate themes in fields like Affine motion, Computation and Outlier.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
ERNEST: a semantic network system for pattern understanding
H. Niemann;G.F. Sagerer;S. Schroder;F. Kummert.
IEEE Transactions on Pattern Analysis and Machine Intelligence (1990)
VERBMOBIL: the use of prosody in the linguistic components of a speech understanding system
E. Noth;A. Batliner;A. Kiessling;R. Kompe.
IEEE Transactions on Speech and Audio Processing (2000)
Model based extraction of articulated objects in image sequences for gait analysis
D. Meyer;J. Denzler;H. Niemann.
international conference on image processing (1997)
Pattern Analysis and Understanding
Automated segmentation of the optic nerve head for diagnosis of glaucoma
Radim Chrástek;Matthias Wolf;Klaus Donath;Heinrich Niemann.
Medical Image Analysis (2005)
Klassifikation von Mustern
A refined ICP algorithm for robust 3-D correspondence estimation
T. Zinsser;J. Schmidt;H. Niemann.
international conference on image processing (2003)
Joint modeling of DNA sequence and physical properties to improve eukaryotic promoter recognition.
Uwe Ohler;Heinrich Niemann;Guo-chun Liao;Gerald M. Rubin.
"Of all things the measure is man" automatic classification of emotions and inter-labeler consistency [speech-based emotion recognition]
S. Steidl;M. Levit;A. Batliner;E. Noth.
international conference on acoustics, speech, and signal processing (2005)
Towards understanding spontaneous speech: word accuracy vs. concept accuracy
M. Boros;W. Eckert;F. Gallwitz;G. Gorz.
international conference on spoken language processing (1996)
Profile was last updated on December 6th, 2021.
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