Algorithms for intelligent fault diagnosis of automated operations offer significant benefits to the manufacturing and process industries. Furthermore, machine learning methods enable such monitoring systems to handle nonlinearities and large volumes of data.
This unique text/reference describes in detail the latest advances in Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use...
Algorithms for intelligent fault diagnosis of automated operations offer significant benefits to the manufacturing and process industries. Furtherm...
This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used as examples to show how each type of problem is related to typical image processing and computer vision problems.
This book presents practical optimization techniques used in image processing and computer vision problems. Ill-posed problems are introduced and used...
Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applications from crowd traffic management to personalised healthcare.
This comprehensive volume is the first work of its kind dedicated to addressing the challenge of Person Re-Identification, presenting insights from an international selection of leading authorities in the field. Taking a strongly multidisciplinary approach, the text provides an in-depth discussion of recent developments and state-of-the-art methods drawn from the...
Re-identification offers a useful tool for non-invasive biometric validation, surveillance, and human-robot interaction in a broad range of applica...
Markov models are extremely useful as a general, widely applicable tool for many areas in statistical pattern recognition.
This unique text/reference places the formalism of Markov chain and hidden Markov models at the very center of its examination of current pattern recognition systems, demonstrating how the models can be used in a range of different applications. Thoroughly revised and expanded, this new edition now includes a more detailed treatment of the EM algorithm, a description of an efficient approximate Viterbi-training procedure, a theoretical derivation of the...
Markov models are extremely useful as a general, widely applicable tool for many areas in statistical pattern recognition.
The pattern recognition and machine learning communities have, until recently, focused mainly on feature-vector representations, typically considering objects in isolation. However, this paradigm is being increasingly challenged by similarity-based approaches, which recognize the importance of relational and similarity information.
This accessible text/reference presents a coherent overview of the emerging field of non-Euclidean similarity learning. The book presents a broad range of perspectives on similarity-based pattern analysis and recognition methods, from purely...
The pattern recognition and machine learning communities have, until recently, focused mainly on feature-vector representations, typically consider...
Video text detection provides an efficient approach to the indexing, classification, retrieval and understanding of visual content.
This unique text/reference presents a systematic introduction to the latest developments in video text detection. Opening with a discussion of the underlying theory and a brief history of video text detection, the text proceeds to cover pre-processing and post-processing techniques, character segmentation and recognition, identification of non-English scripts, techniques for multi-modal analysis, and performance evaluation. The detection of text from...
Video text detection provides an efficient approach to the indexing, classification, retrieval and understanding of visual content.
As data mining algorithms are typically applied to sizable volumes of high-dimensional data, these can result in large storage requirements and inefficient computation times.
This unique text/reference addresses the challenges of data abstraction generation using a least number of database scans, compressing data through novel lossy and non-lossy schemes, and carrying out clustering and classification directly in the compressed domain. Schemes are presented which are shown to be efficient both in terms of space and time, while simultaneously providing the same or better...
As data mining algorithms are typically applied to sizable volumes of high-dimensional data, these can result in large storage requirements and ine...
As the plethora of approaches to biometrics and their deployment continues to grow, so too does the need to combat the techniques used to subvert the aim of such biometric systems.
Presenting the first definitive study of the subject, this Handbook of Biometric Anti-Spoofing reviews the state of the art in covert attacks against biometric systems, and in deriving countermeasures to these attacks. Across a range of common biometrics, including face, iris, fingerprint, speaker and gait, the book describes spoofing methods and examines the vulnerabilities of biometric systems to...
As the plethora of approaches to biometrics and their deployment continues to grow, so too does the need to combat the techniques used to subvert t...
Although the capabilities of computer image analysis do not yet match those of the human visual system, recent developments have made great progress towards tackling the challenges posed by the perceptual analysis of images.
This unique text/reference highlights a selection of important, practical applications of advanced image analysis methods for medical images. The book covers the complete methodology for processing, analysing and interpreting diagnostic results of sample computed tomography (CT) images. The text also presents significant problems related to new approaches and...
Although the capabilities of computer image analysis do not yet match those of the human visual system, recent developments have made great progres...
The combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems in computer vision.
This authoritative text/reference presents an interdisciplinary selection of important, cutting-edge research on RGB-D based computer vision. Divided into four sections, the book opens with a detailed survey of the field, followed by a focused examination of RGB-D based 3D reconstruction, mapping and synthesis. The work continues with a section devoted to novel techniques that employ depth data for object...
The combination of high-resolution visual and depth sensing, supported by machine learning, opens up new opportunities to solve real-world problems...
