This book constitutes the refereed proceedings of the Third International Conference on Intelligence Science, ICIS 2018, held in Beijing China, in November 2018. The 44 full papers and 5 short papers presented were carefully reviewed and selected from 85 submissions. They deal with key issues in intelligence science and have been organized in the following topical sections: brain cognition; machine learning; data intelligence; language cognition; perceptual intelligence; intelligent robots; fault diagnosis; and ethics of artificial intelligence.

Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for Python, Fourth Edition, is focused on the development and implementation of statistically motivated, data-driven techniques for digital image analysis of remotely sensed imagery and it features a tight interweaving of statistical and machine learning theory of algorithms with computer codes. It develops statistical methods for the analysis of optical/infrared and synthetic aperture radar (SAR) imagery, including wavelet transformations, kernel methods for nonlinear classification, as well as an introduction to deep learning in the context of feed forward neural networks. New in the Fourth Edition: An in-depth treatment of a recent sequential change detection algorithm for polarimetric SAR image time series. The accompanying software consists of Python (open source) versions of all of the main image analysis algorithms. Presents easy, platform-independent software installation methods (Docker containerization). Utilizes freely accessible imagery via the Google Earth Engine and provides many examples of cloud programming (Google Earth Engine API). Examines deep learning examples including TensorFlow and a sound introduction to neural networks, Based on the success and the reputation of the previous editions and compared to other textbooks in the market, Professor Canty's fourth edition differs in the depth and sophistication of the material treated as well as in its consistent use of computer codes to illustrate the methods and algorithms discussed. It is self-contained and illustrated with many programming examples, all of which can be conveniently run in a web browser. Each chapter concludes with exercises complementing or extending the material in the text.

Visualization technology is becoming increasingly important for medical and biomedical data processing and analysis. The interaction between visualization and medicine is one of the fastest expanding fields, both scientifically and commercially. This book discusses some of the latest visualization techniques and systems for effective analysis of such diverse, large, complex, and multi-source data.

Digital Imaging Handbook targets anyone with an interest in digital imaging, professional or private, who uses even quite modest equipment such as a PC, digital camera and scanner, a graphics editor such as PAINT, and an inkjet printer. Uniquely, it is intended to fill the gap between the highly technical texts for academics (with access to expensive equipment), and the superficial introductions for amateurs. The four-part treatment spans theory, technology, programs and practice. Theory covers integer arithmetic, additive and subtractive color, greyscales, computational geometry, and a new presentation of discrete Fourier analysis; Technology considers bitmap file structures, scanners, digital cameras, graphic editors, and inkjet printers; Programs develops several processing tools for use in conjunction with a standard Paint graphics editor and supplementary processing tools; Practice discusses 1-bit, greyscale, 4-bit, 8-bit, and 24-bit images for the practice section. Relevant QBASIC code is supplied an accompanying CD and algorithms are listed in the appendix. Readers can attain a level of understanding and the practical insights to obtain optimal use and satisfaction from even the most basic digital-imaging equipment.

The purpose of this volume is to present current work of the Intelligent Computer Graphics community, a community growing up year after year. Indeed, if at the beg- ning of Computer Graphics the use of Artificial Intelligence techniques was quite unknown, more and more researchers all over the world are nowadays interested in intelligent techniques allowing substantial improvements of traditional Computer Graphics methods. The other main contribution of intelligent techniques in Computer Graphics is to allow invention of completely new methods, often based on automation of a lot of tasks assumed in the past by the user in an imprecise and (human) time consuming manner. The history of research in Computer Graphics is very edifying. At the beginning, due to the slowness of computers in the years 1960, the unique research concern was visualisation. The purpose of Computer Graphics researchers was to find new visua- sation algorithms, less and less time consuming, in order to reduce the enormous time required for visualisation. A lot of interesting algorithms were invented during these first years of research in Computer Graphics. The scenes to be displayed were very simple because the computing power of computers was very low. So, scene modelling was not necessary and scenes were designed directly by the user, who had to give co-ordinates of vertices of scene polygons.

Approach your problems from the right end It isn't that they can't see the solution. It is and begin with the answers. Then one day, that they can't see the problem. perhaps you will find the final question. G. K. Chesterton. The Scandal of Father 'The Hermit Clad in Crane Feathers' in R. Brown 'The point of a Pin'. van Gulik's The Chinese Maze Murders. Growing specialization and diversification have brought a host of monographs and textbooks on increasingly specialized topics. However, the "tree" of knowledge of mathematics and related fields does not grow only by putting forth new branches. It also happens, quite often in fact, that branches which were thought to be completely disparate are suddenly seen to be related. Further, the kind and level of sophistication of mathematics applied in various sciences has changed drastically in recent years: measure theory is used (non-trivially) in regional and theoretical economics; algebraic geometry interacts with physics; the Minkowsky lemma, coding theory and the structure of water meet one another in packing and covering theory; quantum fields, crystal defects and mathematical programming profit from homotopy theory; Lie algebras are relevant to filtering; and prediction and electrical engineering can use Stein spaces. And in addition to this there are such new emerging subdisciplines as "experimental mathematics," "CFD," "completely integrable systems," "chaos, synergetics and large-scale order," which are almost impossible to fit into the existing classification schemes. They draw upon widely different sections of mathematics.

After a slow and somewhat tentative beginning, machine vision systems are now finding widespread use in industry. So far, there have been four clearly discernible phases in their development, based upon the types of images processed and how that processing is performed: (1) Binary (two level) images, processing in software (2) Grey-scale images, processing in software (3) Binary or grey-scale images processed in fast, special-purpose hardware (4) Coloured/multi-spectral images Third-generation vision systems are now commonplace, although a large number of binary and software-based grey-scale processing systems are still being sold. At the moment, colour image processing is commercially much less significant than the other three and this situation may well remain for some time, since many industrial artifacts are nearly monochrome and the use of colour increases the cost of the equipment significantly. A great deal of colour image processing is a straightforward extension of standard grey-scale methods. Industrial applications of machine vision systems can also be sub divided, this time into two main areas, which have largely retained distinct identities: (i) Automated Visual Inspection (A VI) (ii) Robot Vision (RV) This book is about a fifth generation of industrial vision systems, in which this distinction, based on applications, is blurred and the processing is marked by being much smarter (i. e. more "intelligent") than in the other four generations."

Games are poised for a major evolution, driven by growth in technical sophistication and audience reach. Characters that create powerful social and emotional connections with players throughout the game-play itself (not just in cut scenes) will be essential to next-generation games. However, the principles of sophisticated character design and interaction are not widely understood within the game development community. Further complicating the situation are powerful gender and cultural issues that can influence perception of characters. Katherine Isbister has spent the last 10 years examining what makes interactions with computer characters useful and engaging to different audiences. This work has revealed that the key to good design is leveraging player psychology: understanding what's memorable, exciting, and useful to a person about real-life social interactions, and applying those insights to character design. Game designers who create great characters often make use of these psychological principles without realizing it. Better Game Characters by Design gives game design professionals and other interactive media designers a framework for understanding how social roles and perceptions affect players' reactions to characters, helping produce stronger designs and better results.

Focusing on how visual information is represented, stored and extracted in the human brain, this book uses cognitive neural modeling in order to show how visual information is represented and memorized in the brain. Breaking through traditional visual information processing methods, the author combines our understanding of perception and memory from the human brain with computer vision technology, and provides a new approach for image recognition and classification. While biological visual cognition models and human brain memory models are established, applications such as pest recognition and carrot detection are also involved in this book. Given the range of topics covered, this book is a valuable resource for students, researchers and practitioners interested in the rapidly evolving field of neurocomputing, computer vision and machine learning.

"Two of the most important trends in sensor development in recent years have been advances in micromachined sensing elements of all kinds, and the increase in intelligence applied at the sensor level. This book addresses both, and provides a good overview of current technology." -- I&CS

Computer vision is becoming increasingly important in several industrial applications such as automated inspection, robotic manipulations and autonomous vehicle guidance. These tasks are performed in a 3-D world and it is imperative to gather reliable information on the 3-D structure of the scene. This book is about passive techniques for depth recovery, where the scene is illuminated only by natural light as opposed to active methods where a special lighting device is used for scene illumination. Passive methods have a wider range of applicability and also correspond to the way humans infer 3-D structure from visual images.

Ambulation Analysis in Wearable ECG

Subhasis Chaudhuri, Tanmay Pawar, Siddhartha Duttagupta

Ambulation Analysis in Wearable ECG demonstrates why, due to recent developments, the wearable ECG recorder substantiates a significant innovation in the healthcare field.

About this book:

• Examines the viability of wearable ECG in cardiac monitoring.
• Includes chapters written by practitioners who have personally developed such hardware to write about the hardware details.
• Bridges the gap between hardware and algorithmic developments with chapters that specifically discuss the hardware aspects and their corresponding calibration issues.
• Presents a useful text for both practitioners and researchers in biomedical engineering and related interdisciplinary fields.
• Assumes basic familiarity with digital signal processing and linear algebra.

The latest generation of visual surveillance systems have adopted recent technological developments in acquisition and communications. These advances have not so much changed the nature of surveillance as extended its reach and reliability. Fundamentally, systems remain relatively unintelligent with human operators remaining central to the threat assessment and response planning procedures found in CCTV installations. Nonetheless, the availability of high-performance computing platforms will ensure that cycle-hungry intellectual property gestating in academic and industrial research programs will have a major impact on the next generation of products. Video-Based Surveillance Systems: Computer Vision and Distributed Processing, surveys works in progress in laboratories from around the world. The first part of the book present the most recent trends in the industrial world including real-time systems for monitoring of indoor and outdoor environments, society infrastructures such as subways and motorways, retail stores and aerial surveillance. Part Two explores current best practices in a chain of algorithms required to perform robust and accurate real-time tracking for motion detection involving rapid and frequent lighting changes, the establishment of accurate temporally consistent object trajectories particularly in crowded scenes, and the classification of object types. Part Three contains contributions which attempt to analyze events unfolding in a monitored scheme. The last part reviews distributed intelligent architectures which are likely to exploit three key recent technological developments in light-weight distributed computing methodologies, and intelligent sensors. Sucharchitectures, in which signal analysis is moving towards sensing devices, can exploit the reduced bandwidth requirements of transmitting knowledge rather than pixels. Video-Based Surveillance Systems: Computer Vision and Distributed Processing provides timely information for professionals working in the areas of surveillance, image processing, computer vision, digital signal processing and telecommunications.

Showcasing the most influential developments, experiments, and architectures impacting the digital, surveillance, automotive, industrial, and medical sciences, Image Processing Technologies tracks the evolution and advancement of computer vision and image processing (CVIP) technologies, examining methods and algorithms for image analysis, optimization, segmentation, and restoration. It focuses on recent approaches and techniques in CVIP applications development and explores various coding methods for individual types of 3-D images. This text/reference brings researchers and specialists up-to-date on the latest innovations affecting multiple image processing environments.

One service mathematics has rendered the tEL moi, .... si j'avait su comment en revenir. je n'y serais point alle'.' human race. It has put common sense back Jules Verne where it belongs, on the topmost shelf next to the dusty canister labelled 'discarded non sense', The series is divergent; therefore we may be Eric T. Bell able to do something with it. O. Heaviside Mathematics is a tool for thought. A highly necessary tool in a world where both feedback and non linearities abound. Similarly, all kinds of parts of mathematics serve as tools for other parts and for other sciences. Applying a simple rewriting rule to the quote on the right above one finds such statements as: 'One service topology has rendered mathematical physics ...'; 'One service logic has rendered com puter science ...'; 'One service category theory has rendered mathematics, ..'. All arguably true. And all statements obtainable this way form part of the raison d'elre of this series."

Image Acquisition and Processing With LabVIEWä combines the general theory of image acquisition and processing, the underpinnings of LabVIEW and the NI Vision toolkit, examples of their applications, and real-world case studies in a clear, systematic, and richly illustrated presentation. Designed for LabVIEW programmers, it fills a significant gap in the technical literature by providing a general training manual for those new to National Instruments (NI) Vision application development and a reference for more experienced vision programmers.

A CD-ROM packaged with the book contains libraries of the example images and code referenced in the text, additional technical white papers, a demonstration version of LabVIEW 6.0, and an NI IMAQ demonstration that guides you through its features.

System Requirements: Using the code provided on the CD-ROM requires LabVIEW 6.1 or higher and LabVIEW Vision Toolkit 6.1 or higher. Some of the examples also require IMAQ Vision Builder 6.1 or higher, the IMAQ OCR toolkit, and IMAQ 1394 drivers.

Human action analyses and recognition are challenging problems due to large variations in human motion and appearance, camera viewpoint and environment settings. The field of action and activity representation and recognition is relatively old, yet not well-understood by the students and research community. Some important but common motion recognition problems are even now unsolved properly by the computer vision community. However, in the last decade, a number of good approaches are proposed and evaluated subsequently by many researchers. Among those methods, some methods get significant attention from many researchers in the computer vision field due to their better robustness and performance. This book will cover gap of information and materials on comprehensive outlook - through various strategies from the scratch to the state-of-the-art on computer vision regarding action recognition approaches. This book will target the students and researchers who have knowledge on image processing at a basic level and would like to explore more on this area and do research. The step by step methodologies will encourage one to move forward for a comprehensive knowledge on computer vision for recognizing various human actions.

The book presents papers delivered by researchers, industrial experts and academicians at the Conference on Emerging Trends in Computing and Communication (ETCC 2014). As such, the book is a collection of recent and innovative works in the field Network Security and Cryptography, Cloud Computing and Big Data Analytics, Data Mining and Data Warehouse, Communication and Nanotechnology and VLSI and Image Processing.

Non-photorealistic rendering (NPR) is a combination of computer graphics and computer vision that produces renderings in various artistic, expressive or stylized ways such as painting and drawing. This book focuses on image and video based NPR, where the input is a 2D photograph or a video rather than a 3D model. 2D NPR techniques have application in areas as diverse as consumer and professional digital photography and visual effects for TV and film production. The book covers the full range of the state of the art of NPR with every chapter authored by internationally renowned experts in the field, covering both classical and contemporary techniques. It will enable both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.

This book proposes a complete pipeline for monocular (single camera) based 3D mapping of terrestrial and underwater environments. The aim is to provide a solution to large-scale scene modeling that is both accurate and efficient. To this end, we have developed a novel Structure from Motion algorithm that increases mapping accuracy by registering camera views directly with the maps. The camera registration uses a dual approach that adapts to the type of environment being mapped. In order to further increase the accuracy of the resulting maps, a new method is presented, allowing detection of images corresponding to the same scene region (crossovers). Crossovers then used in conjunction with global alignment methods in order to highly reduce estimation errors, especially when mapping large areas. Our method is based on Visual Bag of Words paradigm (BoW), offering a more efficient and simpler solution by eliminating the training stage, generally required by state of the art BoW algorithms. Also, towards developing methods for efficient mapping of large areas (especially with costs related to map storage, transmission and rendering in mind), an online 3D model simplification algorithm is proposed. This new algorithm presents the advantage of selecting only those vertices that are geometrically representative for the scene.

Transfer learning is one of the most important technologies in the era of artificial intelligence and deep learning. It seeks to leverage existing knowledge by transferring it to another, new domain. Over the years, a number of relevant topics have attracted the interest of the research and application community: transfer learning, pre-training and fine-tuning, domain adaptation, domain generalization, and meta-learning. This book offers a comprehensive tutorial on an overview of transfer learning, introducing new researchers in this area to both classic and more recent algorithms. Most importantly, it takes a "student's" perspective to introduce all the concepts, theories, algorithms, and applications, allowing readers to quickly and easily enter this area. Accompanying the book, detailed code implementations are provided to better illustrate the core ideas of several important algorithms, presenting good examples for practice.

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15-17 December 2015 in Ho Chi Minh City, Vietnam with the aim of offering researchers, academicians, and practitioners an ideal opportunity to disseminate their findings and achievements. All of the included contributions were chosen by expert peer reviewers from across the world on the basis of their interest to the community. In addition to presenting the latest in design, development, and research, the book provides access to numerous new algorithms for machine learning and signal processing for engineering problems.

Mathematical morphology (MM) is a powerful methodology for the quantitative analysis of geometrical structures. It consists of a broad and coherent collection of theoretical concepts, nonlinear signal operators, and algorithms aiming at extracting, from images or other geometrical objects, information related to their shape and size. Its mathematical origins stem from set theory, lattice algebra, and integral and stochastic geometry. MM was initiated in the late 1960s by G. Matheron and J. Serra at the Fontainebleau School of Mines in France. Originally it was applied to analyzing images from geological or biological specimens. However, its rich theoretical framework, algorithmic efficiency, easy implementability on special hardware, and suitability for many shape- oriented problems have propelled its widespread diffusion and adoption by many academic and industry groups in many countries as one among the dominant image analysis methodologies. The purpose of Mathematical Morphology and its Applications to Image and Signal Processing is to provide the image analysis community with a sampling from the current developments in the theoretical (deterministic and stochastic) and computational aspects of MM and its applications to image and signal processing. The book consists of the papers presented at the ISMM'96 grouped into the following themes: Theory Connectivity Filtering Nonlinear System Related to Morphology Algorithms/Architectures Granulometries, Texture Segmentation Image Sequence Analysis Learning Document Analysis Applications

Thisbookpresentsmaterialwhichismorealgorithmicallyorientedthanmost alternatives.Italsodealswithtopicsthatareatorbeyondthestateoftheart. Examples include practical and applicable wavelet and other multiresolution transform analysis. New areas are broached like the ridgelet and curvelet transforms. The reader will ?nd in this book an engineering approach to the interpretation of scienti?c data. Compared to the 1st Edition, various additions have been made throu- out, and the topics covered have been updated. The background or en- ronment of this book's topics include continuing interest in e-science and the virtual observatory, which are based on web based and increasingly web service based science and engineering. Additional colleagues whom we would like to acknowledge in this 2nd edition include: Bedros Afeyan, Nabila Aghanim, Emmanuel Cand' es, David Donoho, Jalal Fadili, and Sandrine Pires, We would like to particularly - knowledge Olivier Forni who contributed to the discussion on compression of hyperspectral data, Yassir Moudden on multiwavelength data analysis and Vicent Mart' ?nez on the genus function. The cover image to this 2nd edition is from the Deep Impact project. It was taken approximately 8 minutes after impact on 4 July 2005 with the CLEAR6 ?lter and deconvolved using the Richardson-Lucy method. We thank Don Lindler, Ivo Busko, Mike A'Hearn and the Deep Impact team for the processing of this image and for providing it to us.