Book Description
The first edition, published in 1973, has become a classic reference in the field. Now with the second edition, readers will find information on key new topics such as neural networks and statistical pattern recognition, the theory of machine learning, and the theory of invariances. Also included are worked examples, comparisons between different methods, extensive graphics, expanded exercises and computer project topics.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.
Customer Reviews:
Great product & service.......2007-09-21
This was my first purchase from amazon and I was totally impressed by the quality of the product and the service! I would buy again from the same seller and recommend others to do the same.
A Very Bad Sequel.......2007-03-09
I have now used this book 3 times for a class. While the 1st edition did a nice job of covering the material in its time, the additions to in the 2nd addition are a disaster. What the book has going for it is that it at least lists the necessary material for such a course in the table of contents. However, all the additional material is poorly explained at best. The problem sets are too few and the ones that are included are generally weak.
I have tried to use this book, but after constant student complaints and my own difficulty with the text, I have finally concluded that the problem lies with the text and not with the users.
I think an indicator of problems was the large number of errors in the first printing; large here is an understatement. Even in later additions, the 4th, the size of the errata is huge. I think this is indicative of the authors' attention to detail and seriousness in preparation. I have found similar errors and ambiguities in the associate Computer Manual.
The bottom line is that this book has seen its final appearance in our curriculum. I would use any other text, even an older one.
There is simply not enough room or time to point out all the problems with this text. Do yourself a favor if considering this text for a class. Don't bother.
The best book for the discussed field.......2007-02-05
The discussed book is very explanatory and could be students' material for academic lessons.
great book.......2007-01-16
easy to read for computer scientists who are not necessarily experts in statistics. the code in matlab is very good, and helps a lot.
this book is a good introduction to machine learning.
Very well written.......2006-02-26
I liked this book because it does a great job explaining the concepts and the reasoning behind the mathematical formulae. Other books such as "The Elements of Statistical Learning" toss the Math formulas at you and expect you to figure out the significance or the importance of 'em. The book does not shy away from Math - but does a great job presenting it.
Book Description
This volume provides students, researchers and application developers with the knowledge and tools to get the most out of using neural networks and related data modelling techniques to solve pattern recognition problems. Each chapter covers a group of related pattern recognition techniques and includes a range of examples to show how these techniques can be applied to solve practical problems.
Features of particular interest include:
- A NETLAB toolbox which is freely available
- Worked examples, demonstration programs and over 100 graded exercises
- Cutting edge research made accessible for the first time in a highly usable form
- Comprehensive coverage of visualisation methods, Bayesian techniques for neural networks and Gaussian Processes
Although primarily a textbook for teaching undergraduate and postgraduate courses in pattern recognition and neural networks, this book will also be of interest to practitioners and researchers who can use the toolbox to develop application solutions and new models.
"...provides a unique collection of many of the most important pattern recognition algorithms. With its use of compact and easily modified MATLAB scripts, the book is ideally suited to both teaching and research."
Christopher Bishop, Microsoft Research, Cambridge, UK
"...a welcome addition to the literature on neural networks and how to train and use them to solve many of the statistical problems that occur in data analysis and data mining"
Jack Cowan, Mathematics Department, University of Chicago, US
"If you have a pattern recognition problem, you should consider NETLAB; if you use NETLAB you must have this book."
Keith Worden, University of Sheffield, UK
Customer Reviews:
An excellent book too.......2005-03-17
This is actually a must-have book for those who want to study pattern recognition.
excellent tools for implementation of P.R. techniques.......2002-06-25
i first bought the book by Bishop (Neural Network for Pattern Recognition) and anyone who have read it can tell u how excellent that book is. This book has a little bit less theory and more on implementation which is perfect for me. This book include all the topics covered in Bishop and then some. How the book is organized, and how concise, easy to understand the material is at the same amazing level as Bishop's. I believe implementing and practicing things u learn is key to understanding them.. if you just look at how things are implemented, things would suddenly become 10 times clearer for you.. often to your own amazement (that you can actually understand all those stuff). this book is extremely useful even if u dont have matlab (just look up the syntax at mathworks web site), cuz matlab code is straightforward to understand. and the material included is very up to date and cutting edge indeed. i highly highly recommend it.
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Digital Image Analysis: Selected Techniques and Applications
Manufacturer: Springer
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ASIN: 0387950664 |
Book Description
This book presents a broad-ranging edited survey of computational and analytical methods and tools for digital image analysis and interpretation. The book brings together the recent results and methods in a uniform manner, thereby making the information accessible to nonspecialists and specialists alike. Topics and features: * Diverse topics are treated in an integrative style, using a common notation * With theory and applications covered in a single volume, the reader sees immediately that the proposed methods also work in practice * Overview of some key research in digital image processing and pattern recognition methods and tools * Up-to-date coverage of current topics: information fusion, stochastic shape theory, graph-based image analysis and hierarchical systems The book offers a uniquely comprehensive technical survey that not only provides in-depth coverage of the fundamental topics in the field, but also incorporates the newest developments that have arisen. It serves as an excellent and current resource for researchers, practitioners and professionals in computer science and electrical engineering focusing on methodology for digital imaging and analysis.
Book Description
Embedded Image Processing on the TMS320C6000™ DSP: Examples in Code Composer Studio™ and MATLAB focuses on efficient implementations of advanced image processing algorithms for resource-constrained embedded DSP systems. Featuring the popular Texas Instruments TMS320C6000TM line of Digital Signal Processors, it utilizes a proven methodology of beginning with a high-level algorithmic point-of-view, proceeding to develop prototype code in MATLAB and Visual Studio, and concluding with an efficient implementation suitable for deployment on an embedded DSP system.
Aside from image processing, the author also explains the uses and rationale behind a plethora of technologies, most notably several industry-standard and essential TI developer technologies, including the Code Composer Studio™ IDE. Highlights include numerous debugged MATLAB and C/C++ Visual Studio prototype applications and efficient C implementations of real-world algorithms tested on both the C6416 DSK and C6701 EVM development platforms.
Packaged with the book is a CD-ROM which includes the source code, tested and debugged using the latest versions of developer tools, as well as sample image data. The CD-ROM contains a number of projects, spanning a diverse range of image processing applications such as, spatial processing techniques, image filtering, edge detection and segmentation schemes, and wavelet-based algorithms, among others.
Embedded Image Processing on the TMS320C6000™ DSP: Examples in Code Composer Studio™ and MATLAB is an essential book for professional signal & image processing engineers working with TI DSPs where real-time constraints are present and performance is at a premium. Imaging software developers and DSP users will also find this book applicable, as it covers a variety of image and signal processing building blocks that appear in a diverse set of real-world applications, including medical imaging, satellite imaging, digital photography, and pattern recognition, to name a few. It may also serve as a reference work for advanced image processing, computer vision, and DSP students working in labs that use TI development kits or MATLAB.
Customer Reviews:
Images and more..........2005-10-28
There are many great examples of basic image processing techniques in this book. Topics like Image Filtering, Edge Detection and also some Wavelets. There is both theory and detailed examples which really helps when trying to get the DSP in a symbiotic relationship with Matlab, CodeComposer Studio and MS Visual Studio.
There is a logical flow in how information is presented. First a basic description of the algorithm. Second some Matlab or pseudo-code. Then third he describes exactly how to implement it on the c6x dsp. Not only are there implementation details but also interfacing explanation for both Matlab and Visual Studio.
Overall this is an excellent book for getting a project up and running in a timely fashion.
A well laid out introduction to embedded image processing.......2005-08-13
This is an extremely well laid out and understandable text. The coding examples are easy to understand and can be easily demonstrated on the TI DSK's. As a current TI employee with little experience with the C6x line of DSP's, Qureshi's book allowed me to learn a large amount of image processing background in a short time while becoming familiar with the workings of Code Composer Studio and the DSP. The book starts very simply and has clear instructions on how to obtain the tools to run all of the code samples on real DSPs.
Starting with an overview of the tools involved and the C6x architecture, Qureshi moves into simple image processing concepts, such as contrast stretching and window/level processing. After clearly explaining the concept and the implementation, the reader is led through the process of optimizing the code for the DSP environment. Later topics, such as edge detection and wavelets leave the reader with a clear understanding of the fundamentals of image processing, as well as code examples that make implementation a breeze.
Overall, an excellently written book and a must for anyone interested in image processing, whether on TI DSPs or not.
Average customer rating:
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Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers, Scientists and Mathematicians (Springer International Series in Engineering and Computer Science)
Marvin K. Simon
Manufacturer: Springer
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ASIN: 0387346570 |
Book Description
This handbook, now available in paperback, brings together a comprehensive collection of mathematical material in one location. It also offers a variety of new results interpreted in a form that is particularly useful to engineers, scientists, and applied mathematicians. The handbook is not specific to fixed research areas, but rather it has a generic flavor that can be applied by anyone working with probabilistic and stochastic analysis and modeling.
- Classic results are presented in their final form without derivation or discussion, allowing for much material to be condensed into one volume.
- Concise compilation of disparate formulae saves time in searching different sources
- Focused application has broad interest for many disciplines: engineers, computer scientists, statisticians, physicists; as well as any researcher working in probabilistic and stochastic analysis and modeling in the natural or social sciences.
- The material is timeless and has intrinsic value to today’s and tomorrow’s practicing engineers and scientists
- Endorsed by top experts in field worldwide, ensuring quality and value
Excerpts from reviews of the hardbound edition:
The reference book "Probability Distributions Involving Gaussian Random Variables," authored by Dr. Marvin Simon, has become, in a very short time frame, one of the most useful aids to research in the field of digital communications that has come out in many years. It has replaced various other well known resources because of its concentration of relevant, timely, and easily accessible results. —Dr. Larry Milstein, UCSD
This is a unique book and an invaluable reference for engineers and scientists in the fields of electrical engineering, mathematics and statistics. There is no other single reference book that covers Gaussian and Gaussian-related distributions of random variables that are encountered in research work and practice. This is a reference book that I recommend to all my graduate students working in the area of telecommunication system analysis and design. —Dr. John Proakis, Northeastern University and UCSD
… this book collected all these results (after double-checking them) with unified notations and in an organized fashion made it very useful for many of the graduate students and researchers doing analytical type of investigations. Not only did I use it, I also recommend it to my graduate students and many of our papers benefited from the formulas available in the handbook…. The handbook saves valuable time for all the researchers that rely on it to simplify their results or write them in terms of well-known functions that are available in popular mathematical packages such as Matlab and Mathematica. —Dr. Mohamed-Slim Alouini, Texas A&M University
The distributions and associated statistics described in the book apply to systems like mobile and cellular communications, vehicular technology, radar systems, spread spectrum systems, and optical communication systems. The book, with its comprehensive information in analytical, tabular, and graphical form, is an invaluable tool for scientists and engineers. —Dr. Sergio Benedetto, Politecnico di Torino
The book "Probability Distributions Involving Gaussian Random Variables" is a handy research reference in areas such as communication systems. I have found the book useful for my own work, since it presents probability distributions that are difficult to find elsewhere and that have non-obvious derivations. —Dr. Gordon Stüber, Georgia Institute of Technology
A unique and invaluable reference for researchers in communications, signal processing, math, statistics, and many other scientific fields. I have used this book in my own research and also recommended it to colleagues in universities and in industry, as well as to graduate students. —Dr. Andrea Goldsmith, Stanford University
In my research in wireless communications, I have often found that I can get all the mathematical forms and material that I need from one source, where before I had to consult five or six references to get the complete information. There are a small number of reference works that have proved so invaluable that I have purchased a home copy in addition to my office copy. This handbook is one of them. —Dr. Norman C. Beaulieu, University of Alberta
Our research Group at the University of Canterbury is engaged in both theoretical and experimental work on advanced wireless communications systems. We have found that the book by Simon, "Probability Distributions Involving Gaussian Random Variables" is an indispensable and often used reference for this work. We do significant amounts of analysis involving Gaussian statistics and quadratic forms. The book is the one source that brings almost all of the necessary background material together in a readily usable form and is thus an extremely valuable reference. —Dr. Desmond P. Taylor, University of Canterbury
Dr. Simon's book is by far the most comprehensive compilation of Gaussian probability distributions and their associated statistics - in fact to my knowledge this is the only book of its type in publication now. This handbook is a much needed and most welcome entry to the toolbox of any engineer or scientist. For those working in digital and wireless communications, signal and image processing, pattern recognition, and many other technical fields, the text is absolutely essential. —Payman Arabshahi, Applied Physics Laboratory
As a researcher and teacher in the digital communication theory area for the last forty years, I can state that Simon’s book contains materials in his ten chapters and appendices most relevant to researchers and developers of modern communication systems. These sophisticated Gaussian related expressions are needed in the analysis, design, and optimization of modern microwave and cellular communications. Many of these results are unavailable elsewhere, since these results were originated by Simon himself. —Dr. Kung Yao, UCLA
After I spent a few minutes trying to come up with my own derivation, I decided to consult Probability Distributions Involving Gaussian Random Variables, where I found the needed result within a few seconds. On this and many other occasions, I have found Marvin Simon's book to be a unique and extremely valuable resource for my own research. The book is even more crucial for the graduate students who, unlike those in my generation, did not grow up with the Gaussian Q function, Marcum's Q-function, Rayleigh and Rician distributions, chi-squared random variables, and all the other important functions, distributions, and concepts that have their roots in Gaussian random variables. —Dr. Michael B. Pursley, Clemson University
Because the source of randomness and noise is usually modeled as Gaussian, engineers and scientists often need the probability distributions of functions of Gaussian random variables. Marvin Simon has written an extremely useful handbook for everyone working in these fields. It is by far the most complete and easy-to-use collection of these characterizations of functions of Gaussian random variables. …an important and very popular book that is useful to a very large community of engineers and scientists. This work is also very carefully done with many corrections to earlier works that were not easily available to this community. —Jim Omura, Technology Strategist, Gordon and Betty Moore Foundation
The handbook "Probability Distributions Involving Gaussian Random Variables" by Marvin K. Simon is a wonderful resource for both theoreticians and practitioners in that it contains a wealth of information summarized in one book. —Dr. Costas N. Georghiades, Texas A&M University
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Svd and Signal Processing: Algorithms, Applications and Architectures
E. F. Deprettere
Manufacturer: North-Holland
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ASIN: 0444704396 |
Book Description
Image synthesis, or rendering, is a field of transformation: it changes
geometry and physics into meaningful images. Because the most popular
algorithms frequently change, it is increasingly important for researchers
and implementors to have a basic understanding of the principles of image
synthesis. Focusing on theory, Andrew Glassner provides a comprehensive
explanation of the three core fields of study that come together to form
digital image synthesis: the human visual system, digital signal
processing, and the interaction of matter and light. Assuming no more than
a basic background in calculus, Glassner transforms his passion and
expertise into a thorough presentation of each of these disciplines, and
their elegant orchestration into modern rendering techniques such as
radiosity and ray tracing.
Customer Reviews:
Finally, I get this book:).......2007-06-08
I have not read this book throughly yet, but I have long
been hoping get this book to read and finally I get it.
It must be a good fundamental image synthesis book because
I remember once some graphics guru recommend this book
to me strongly, but forget when and who:)
Disappointed.......2003-09-03
I was expecting much more out of this 2 volume set. The books are full of mistakes, especially in formulas. If you plan on purchasing these books, make sure to download and print out the errata as well. It could save many headaches in trying to understand formulas that don't agree with the accompanying explanation. I don't doubt that Glassner is a very intelligent man, but his descriptions are somewhat dense and difficult to decypher sometimes. My recommendation: get an ACM SIGGRAPH membership to get access to many of the papers in this field and get the algorithms straight from the source.
Great Book.......2002-11-09
Among all of the CG books on my shelf, this is the only one which binds the CG subjects to physics origin so deeply. Glassner prepared a very nice collection of reference information, explained the historical reasons of several confusing stuff in CG.
It's true that it has number of mistakes / typos but there's an online errata .... Once you check and note down the errata in the proper places of the book - which may take your 1hr at the most-, nothing will remain to complain about this book.
If you are serious about CG, you'll love the information in this book. It's a bit expensive but surely worth the price.
Excellent.......2001-10-15
Volume 1:
This book is comprehensive in scope and one of the most well-written technical books in existence. In the preface the author states 'I love to write', and considering the exceptional quality of this book, this indeed shows through.
The first part of the book covers the human visual system, the understanding of which is fundamental to designing effective computer graphics. Several interesting topics are discussed, including Mach bands, color opponency, perceptual color matching, MacAdam ellipses, RGB color space, and gamut mapping.
The second part covers more technical matters, namely that of signal processing. The mathematical background assumed of the reader increases dramatically in this part; some exposure to elementary calculus and differential equations would suffice. The author does a good job of explaining such concepts as linear operators and the Dirac bracket notation. The pictorial representation he gives of the convolution operation is very helpful. In addition, Fourier analysis is presented at a level that makes it very clear exactly what is happening to signals, both discrete and continuous, when taking the Fourier transform. The Fast Fourier transform is not discussed however, dissapointingly. Suprisingly, a whole chapter is devoted to wavelet transforms, a topic usually not included at this level. Wavelets are used as a tool to deal with nonstationary signals. Usually discussed at a very abstract level, the presentation here is crystal clear and vey intutive, and the reader will take away a deeper appreciation of these objects than what could have been obtained from the usual presentations.
Chapter 7 is one of the most important in the book for it covers Monte Carlo techniques for evaluating the integrals that arise in image processing. The speed of convergance of Monte Carlo is addressed, along with how to estimate confidence levels when the parent distribution is normal. The author presents five different ways of doing 'blind' Monte Carlo, including rejection, blind stratified, weighted, and quasi Monte Carlo. Quasi Monte Carlo has taken on particular importance in recent years wherever Monte Carlo techniques are used. The author also presents four different ways of doing 'informed' Monte Carlo, i.e. when some information about the signal is known.
Uniform sampling of continuous signals is done in the next chapter. After discussing an example of sampling and reconstruction, the author outlines in detail the mathematical theory behind the uniform sampling and reconstruction of one-and two-dimensional signals. The chapter ends with a discussion of a technique to reduce aliasing artifacts called supersampling.
The next chapter covers nonuniform sampling and reconstruction. Naturally this is more complicated from a mathematical standpoint, due to the role of stochastic processes, but the author does a good job of discussing the relevant concepts. Most interesting is his treatment of the duality between aliasing and noise.
Chapter 10 surveys some of the more modern and practical techniques used for sampling and reconstruction of two-dimensional signals. Uniform sampling is discussed in terms of rectangular and hexagonal lattices; nonuniform sampling in terms of Poisson sampling and N-books sampling. Pseudocode is given for the decreasing radius algorithm. The concept of a refinement test is introduced and broken down into five categories, each of which is discussed in detail. The refinement test allows one to decide when more samples are needed in a neighborhood, and refinement geometry indicates where the samples are to be placed. Refinement geometry is discussed in this chapter also, with linear and area bisection techniques outlined, along with multiple-level and tree-based sampling. Techniques for interpolation and reconstruction, such as warping are also treated, and the author gives brief overviews of one-dimensional and two-dimensional sampling theorems. Numerous other methods, going by several different names are also discussed.
A very large set of references is given at the end of the book, covering a wide variety of topics in computer graphics and mathematical formalism. I have not read the second volume, but I am sure it respects the high quality of the first.
Graphics is Math, Physics, Perception, & Computation.......2000-11-11
Back in the old days, Computer Graphics was a big bag of tricks for making cool images. To make the pictures look better and better, the research community stumbled into areas we didn't originally know were important. We now see that clipping, viewports, line-drawing, and specular lights are not so fundamental. Instead, we're understanding that items in the bag of graphics tricks were often shortcuts to solving an integral equation for heat transfer. Who would have thought it?
This textbook is the first comprehensive treatment of Computer Graphics to convey the deeper understanding that researchers have finally begun to make peace with. It's not always easy. That marginal lecture on de-aliasing in your graphics class? It turns out to be hugely significant. Sampling and reconstruction pervade graphics algorithms, and the first 10 chapters cover the topic extensively. That reflectance distribution function you saw at the end of the semester? It's not an advanced topic. It's what realistic rendering is built from. How to represent it, evaluate it, and integrate it are the concerns of the next 10 chapters.
The hypothetical Ideal Graphics Professional has majored in Math, Computer Science, Physics, Perceptual Psychology, and Mechanical Engineering. No one has that background, but if you majored in any of these subjects and then patiently read this book, you will appreciate how the themes combine in a remarkable way whenever a pixel is drawn.
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Industrial Image Processing: Visual Quality Control in Manufacturing
Christian Demant ,
Bernd Streicher-Abel , and
Peter Waszkewitz
Manufacturer: Springer
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Level Set Methods and Dynamic Implicit Surfaces
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Interactive Panoramas: Techniques for Digital Panoramic Photography (X.media.publishing)
ASIN: 3540664106 |
Book Description
This practical introduction focuses on how to build integrated solutions to industrial vision problems from individual algorithms. It gives a hands-on guide for setting up automated visual inspection systems using real-world examples and the NeuroCheck software package. This software is used for on-line visual inspection in many industrial production processes. Based on many years of experience in industries, the editors explain all the (mostly unpublished but essential) details encountered in the creation of real-world vision systems. With the original NeuroCheck software package and all the example images included on CD-ROM, readers can work their way through the described inspection tasks and carry out their own experiments.
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- Timeless Fundamentals of Halftoning
- Good, but not the only book you will need.
- *The* Book for Digital Imaging
- excellent book
|
Digital Halftoning
Robert Ulichney
Manufacturer: The MIT Press
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Digital Color Halftoning (SPIE Press Monograph Vol. PM68)
ASIN: 0262210096 |
Book Description
Along with text and graphics, images are fast becoming a generic data type for general-purpose computer systems. This poses new problems for the systems designer, who must be able to preprocess digital image data for a wide variety of video and hard copy displays. Digital halftoning, the method by which the illusion of continuous-tone images are created through the arrangement of binary picture elements, is a key component of any preprocessing.
Digital Halftoning addresses the problem of developing algorithms that best match the specific parameters of any target display device. It is the first significant study of the process of producing quality images on practical computer displays.
To aid the systems designer, Ulichney devises the concept of blue noise - which has many desirable properties for halftoning - and suggests efficient algorithms for its use. He also introduces new metrics for analyzing the frequency content of periodic and aperiodic patterns for both rectangular and hexagonal grids, and presents a unique "aspect ratio immunity" argument in favor of hexagonal grids. Included are several carefully selected digitally-produced images.
Robert Ulichney is Principle Engineer with the Digital Equipment Corporation.
Customer Reviews:
Timeless Fundamentals of Halftoning.......2003-11-15
It seems that everyone working in halftoning has or references this book. While there are certainly newer texts on this subject, this book continues to be the key reference for developers and researchers in the field. It is in this book that the theory and definitions of blue noise, now a central concept in halftoning, are introduced. Published in 1987, this text is certainly missing developments since then, and does not cover color issues. However, the passage of time has proven its importance as evidenced by continued and widespread reference to it; it remains an excellent resource for its presentation of foundations and fundamentals that have not changed.
Good, but not the only book you will need........2003-07-23
This book does contain some useful information, unfortunately the author seems to asume that the reader has considerable experience with the subject. Most of the information though is quite outdated as the book does not touch on any of the newer techniques. I also feel that the book does not explain the subject matter enough to be able to write software implementations, and more than once I have had to go looking elsewhere for more information. In a nutshell, it is a good 'reference book for certain topics', and i'd advise you to borrow it from a library instead of purchasing it.
*The* Book for Digital Imaging.......2000-06-11
If you are interested in Digital Imaging this is your best bet to get started. Every halftoning technique invented so far is reviewed and presented in an easy and understandable fashion.
excellent book.......2000-06-10
I have been made a thesis about the binary algorthim on my degree thesis . This book helped me a lot.Really.
Average customer rating:
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Hexagonal Image Processing: A Practical Approach (Advances in Pattern Recognition)
Lee Middleton , and
Jayanthi Sivaswamy
Manufacturer: Springer
ProductGroup: Book
Binding: Hardcover
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ASIN: 1852339144 |
Book Description
This book provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates.
The strengths offered by hexagonal lattices over square lattices to define digital images are considerable:
- higher packing density
- uniform connectivity of points (pixels) in the lattice
- better angular resolution by virtue of having more nearest neighbours
- superlative representation of curves
The utility of the HIP framework is shown by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. Theory and algorithms are covered as well as details such as accommodating hardware that support only images sampled on a square lattice. A CD-ROM provides code enabling the reader to develop and test algorithms for processing hexagonal images.
This fresh approach offers insight and workable know-how to both researchers and postgraduates.
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