Markov Models for Pattern Recognition by Gernot A Fink
describes important methods for efficient processing of Markov models, and the adaptation of the models to different tasks; examines algorithms for searching within the complex solution spaces that result from the joint application of Markov chain and hidden Markov models;-
NETLAB
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Multimodal Collaborative Perception for Unmanned Systems
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Advances in Photometric 3D-Reconstruction
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Active Lighting and Its Application for Computer Vision
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Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics
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Selfie Biometrics
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Handbook of Vascular Biometrics
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Natural User Interfaces in Medical Image Analysis
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Advanced Algorithmic Approaches to Medical Image Segmentation
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Statistical Learning and Pattern Analysis for Image and Video Processing
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An Introduction to Object Recognition
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Human Recognition at a Distance in Video
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Nonlinear Eigenproblems in Image Processing and Computer Vision
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Autonomous Intelligent Vehicles
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Similarity-Based Pattern Analysis and Recognition
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Hyperspectral Image Analysis
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Guide to OCR for Indic Scripts
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Automatic Digital Document Processing and Management
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Multispectral Satellite Image Understanding
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Guide to Three Dimensional Structure and Motion Factorization
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Machine Learning for Vision-Based Motion Analysis
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Handbook of Remote Biometrics
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Fusion in Computer Vision
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Compression Schemes for Mining Large Datasets
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Shape Perception in Human and Computer Vision
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Imaging Spectroscopy for Scene Analysis
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Visual Question Answering
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Tensors in Image Processing and Computer Vision
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Handbook of Biometric Anti-Spoofing
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Computer Vision Beyond the Visible Spectrum
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Image Registration
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Statistical and Neural Classifiers
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Contactless 3D Fingerprint Identification
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Hierarchical Perceptual Grouping for Object Recognition
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Adaptive Biometric Systems
From the book reviews:
“The book is highly appropriate for researchers and practitioners dealing with pattern recognition in general and speech, character and handwriting recognition sequences, in particular” (Catalin Stoean, zbMATH 1307.68001, 2015)
Gernot A. Fink earned his diploma in computer science from the
University of Erlangen-Nuremberg, Erlangen, Germany, in 1991.
He recieved a Ph.D. degree in computer science in 1995 and
the venia legendi in applied computer science in 2002 both
from Bielefeld University, Germany.
Currently, he is professor for Pattern Recognition in Embedded Systems
at the University of Dortmund, Germany, where he also heads the
Intelligent Systems Group at the Robotics Research Institute.
His reserach interests lie in the development and application of
pattern recognition methods in the fields of man machine interaction,
multimodal machine perception including speech and image processing,
statistical pattern recognition, handwriting recognition, and the
analysis of genomic data.
University of Erlangen-Nuremberg, Erlangen, Germany, in 1991.
He recieved a Ph.D. degree in computer science in 1995 and
the venia legendi in applied computer science in 2002 both
from Bielefeld University, Germany.
Currently, he is professor for Pattern Recognition in Embedded Systems
at the University of Dortmund, Germany, where he also heads the
Intelligent Systems Group at the Robotics Research Institute.
His reserach interests lie in the development and application of
pattern recognition methods in the fields of man machine interaction,
multimodal machine perception including speech and image processing,
statistical pattern recognition, handwriting recognition, and the
analysis of genomic data.
| SKU | Unavailable |
| ISBN 13 | 9781447163077 |
| ISBN 10 | 1447163079 |
| Title | Markov Models for Pattern Recognition |
| Author | Gernot A Fink |
| Series | Advances In Computer Vision And Pattern Recognition |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | Springer London Ltd |
| Year published | 2014-01-28 |
| Number of pages | 276 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |