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Author: Prasanta Sahoo Publisher: Springer Science & Business Media ISBN: 3642179223 Category : Technology & Engineering Languages : en Pages : 86
Book Description
The concept of fractals is often considered to describe surface roughness. Fractals retain all the structural information and are characterized by a single descriptor, the fractal dimension, D. Fractal dimension is an intrinsic property of the surface and independent of the filter processing of measuring instrument as well as the sampling length scale. This book cover fractal analysis of surface roughness in different machining processes such as Computer Numeric Control (CNC) end milling, CNC turning, electrical discharge machining and cylindrical grinding. The content here presented adds a significant contribution to the existing literature, with interest to both industrial and academic public.
Author: Prasanta Sahoo Publisher: Springer Science & Business Media ISBN: 3642179223 Category : Technology & Engineering Languages : en Pages : 86
Book Description
The concept of fractals is often considered to describe surface roughness. Fractals retain all the structural information and are characterized by a single descriptor, the fractal dimension, D. Fractal dimension is an intrinsic property of the surface and independent of the filter processing of measuring instrument as well as the sampling length scale. This book cover fractal analysis of surface roughness in different machining processes such as Computer Numeric Control (CNC) end milling, CNC turning, electrical discharge machining and cylindrical grinding. The content here presented adds a significant contribution to the existing literature, with interest to both industrial and academic public.
Author: Fernando Brambila Publisher: BoD – Books on Demand ISBN: 9535131915 Category : Mathematics Languages : en Pages : 296
Book Description
Fractal analysis has entered a new era. The applications to different areas of knowledge have been surprising. Let us begin with the fractional calculus-fractal geometry relationship, which allows for modeling with extreme precision of phenomena such as diffusion in porous media with fractional partial differential equations in fractal objects. Where the order of the equation is the same as the fractal dimension, this allows us to make calculations with enormous precision in diffusion phenomena-particularly in the oil industry, for new spillage prevention. Main applications to industry, design of fractal antennas to receive all frequencies and that is used in all cell phones, spacecraft, radars, image processing, measure, porosity, turbulence, scattering theory. Benoit Mandelbrot, creator of fractal geometry, would have been surprised by the use of fractal analysis presented in this book: "Part I: Petroleum Industry and Numerical Analysis"; "Part II: Fractal Antennas, Spacecraft, Radars, Image Processing, and Measure"; and "Part III: Scattering Theory, Porosity, and Turbulence." It's impossible to picture today's research without fractal analysis.
Author: Matti Pietikinen Publisher: World Scientific ISBN: 9789810243739 Category : Computers Languages : en Pages : 284
Book Description
d104ure analysis is an important generic research area of machine vision. The potential areas of application include biomedical image analysis, industrial inspection, analysis of satellite or aerial imagery, content-based retrieval from image databases, document analysis, biometric person authentication, scene analysis for robot navigation, texture synthesis for computer graphics and animation, and image coding. d104ure analysis has been a topic of intensive research for over three decades, but the progress has been very slow.A workshop on ?d104ure Analysis in Machine Vision? was held at the University of Oulu, Finland, in 1999, providing a forum for presenting recent research results and for discussing how to make progress in order to increase the usefulness of texture in practical applications. This book contains extended and revised versions of the papers presented at the workshop. The first part of the book deals with texture analysis methodology, while the second part covers various applications. The book gives a unique view of different approaches and applications of texture analysis. It should be of great interest both to researchers of machine vision and to practitioners in various application areas.
Author: Muthukumaran Malarvel Publisher: John Wiley & Sons ISBN: 1119786096 Category : Computers Languages : en Pages : 354
Book Description
Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.
Author: Alessandro E.P. Villa Publisher: Springer ISBN: 3319447815 Category : Computers Languages : en Pages : 580
Book Description
The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions. They were organized in topical sections named: from neurons to networks; networks and dynamics; higher nervous functions; neuronal hardware; learning foundations; deep learning; classifications and forecasting; and recognition and navigation. There are 47 short paper abstracts that are included in the back matter of the volume.
Author: John A. Meech Publisher: DEStech Publications, Inc ISBN: 9781932078190 Category : Business & Economics Languages : en Pages : 990
Book Description
Offers research for software and hardware developed to produce and process materials using higher-level automatic and intelligent systems.
Author: Milan Sonka Publisher: Springer ISBN: 148993216X Category : Computers Languages : en Pages : 579
Book Description
Image Processing, Analysis and Machine Vision represent an exciting part of modern cognitive and computer science. Following an explosion of inter est during the Seventies, the Eighties were characterized by the maturing of the field and the significant growth of active applications; Remote Sensing, Technical Diagnostics, Autonomous Vehicle Guidance and Medical Imaging are the most rapidly developing areas. This progress can be seen in an in creasing number of software and hardware products on the market as well as in a number of digital image processing and machine vision courses offered at universities world-wide. There are many texts available in the areas we cover - most (indeed, all of which we know) are referenced somewhere in this book. The subject suffers, however, from a shortage of texts at the 'elementary' level - that appropriate for undergraduates beginning or completing their studies of the topic, or for Master's students - and the very rapid developments that have taken and are still taking place, which quickly age some of the very good text books produced over the last decade or so. This book reflects the authors' experience in teaching one and two semester undergraduate and graduate courses in Digital Image Processing, Digital Image Analysis, Machine Vision, Pattern Recognition and Intelligent Robotics at their respective institutions.
Author: Victor E. Staartjes Publisher: Springer Nature ISBN: 303085292X Category : Medical Languages : en Pages : 343
Book Description
This book bridges the gap between data scientists and clinicians by introducing all relevant aspects of machine learning in an accessible way, and will certainly foster new and serendipitous applications of machine learning in the clinical neurosciences. Building from the ground up by communicating the foundational knowledge and intuitions first before progressing to more advanced and specific topics, the book is well-suited even for clinicians without prior machine learning experience. Authored by a wide array of experienced global machine learning groups, the book is aimed at clinicians who are interested in mastering the basics of machine learning and who wish to get started with their own machine learning research. The volume is structured in two major parts: The first uniquely introduces all major concepts in clinical machine learning from the ground up, and includes step-by-step instructions on how to correctly develop and validate clinical prediction models. It also includes methodological and conceptual foundations of other applications of machine learning in clinical neuroscience, such as applications of machine learning to neuroimaging, natural language processing, and time series analysis. The second part provides an overview of some state-of-the-art applications of these methodologies. The Machine Intelligence in Clinical Neuroscience (MICN) Laboratory at the Department of Neurosurgery of the University Hospital Zurich studies clinical applications of machine intelligence to improve patient care in clinical neuroscience. The group focuses on diagnostic, prognostic and predictive analytics that aid in decision-making by increasing objectivity and transparency to patients. Other major interests of our group members are in medical imaging, and intraoperative applications of machine vision.
Author: Jan Novotny Publisher: John Wiley & Sons ISBN: 1119404754 Category : Business & Economics Languages : en Pages : 640
Book Description
Upgrade your programming language to more effectively handle high-frequency data Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Ideally designed to handle the speed and volume of high-frequency financial data at sell- and buy-side institutions, these tools have become the de facto standard; this book provides the foundational knowledge practitioners need to work effectively with this rapidly-evolving approach to analytical trading. The discussion follows the natural progression of working strategy development to allow hands-on learning in a familiar sphere, illustrating the contrast of efficiency and capability between the q language and other programming approaches. Rather than an all-encompassing “bible”-type reference, this book is designed with a focus on real-world practicality to help you quickly get up to speed and become productive with the language. Understand why kdb+/q is the ideal solution for high-frequency data Delve into “meat” of q programming to solve practical economic problems Perform everyday operations including basic regressions, cointegration, volatility estimation, modelling and more Learn advanced techniques from market impact and microstructure analyses to machine learning techniques including neural networks The kdb+ database and its underlying programming language q offer unprecedented speed and capability. As trading algorithms and financial models grow ever more complex against the markets they seek to predict, they encompass an ever-larger swath of data – more variables, more metrics, more responsiveness and altogether more “moving parts.” Traditional programming languages are increasingly failing to accommodate the growing speed and volume of data, and lack the necessary flexibility that cutting-edge financial modelling demands. Machine Learning and Big Data with KDB+/Q opens up the technology and flattens the learning curve to help you quickly adopt a more effective set of tools.
Author: Prasanta Sahoo
Author: Prasanta Sahoo
Author: Fernando Brambila
Author: Matti Pietikinen
Author: Muthukumaran Malarvel
Author: Alessandro E.P. Villa
Author: Kathryn Hess
Author: John A. Meech
Author: Milan Sonka
Author: Victor E. Staartjes
Author: Jan Novotny