Download or read book Fast Learning and Invariant Object Recognition written by Branko Soucek and published by Wiley-Interscience. This book was released on 1992-05-07 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This applications-oriented book presents, for the first time, Learning-Generalization-Seeing-Recognition Hybrids. Numerous new learning algorithms are described, including holographic networks, adaptive decoupled momentum, feature construction, second-order gradient, and adaptive-symbolic methods. Object recognition systems in real-time applications are presented and include massively parallel and systolic array implementations. These systems exhibit up to 2 billion operations and over 300 billion connections per second. Position, scale and rotation invariant systems for industrial machine vision are presented, including testing of IC chips; flying object recognition; space shuttle and aircraft experiments; detection of moving objects; shape recognition in manufacturing; recognition of occluded objects; biomedical image classification; three-dimensional ultrasonic imaging in clinical ophthalmology, and others. New invariant object recognition paradigms include orthogonal sets of feature layers; higher-order neural networks; detection of movement-attention-tracking; landmark matching; segmentation of three-dimensional images; dynamic links on the reduced mesh of trees. Fast Learning and Invariant Object Recognition presents a unified treatment of material that has previously been scattered worldwide in a number of research reports, as well as previously unpublished methods and results from the IRIS (Integration of Reasoning, Informing and Serving) Group.
Download or read book Proceedings of the Fifteenth Annual Conference of the Cognitive Science Society written by Science Society Cognitive, Con and published by Psychology Press. This book was released on 1993 with total page 1080 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features the complete text of all regular papers, posters, and summaries of symposia presented at the 15th annual meeting of the Cognitive Science Society.
Download or read book System and Circuit Design for Biologically Inspired Intelligent Learning written by Temel, Turgay and published by IGI Global. This book was released on 2010-10-31 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The objective of the book is to introduce and bring together well-known circuit design aspects, as well as to cover up-to-date outcomes of theoretical studies in decision-making, biologically-inspired, and artificial intelligent learning techniques"--Provided by publisher.
Download or read book Predictions in the Brain written by Moshe Bar and published by Oxford University Press. This book was released on 2011-05-10 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: When one is immersed in the fascinating world of neuroscience findings, the brain might start to seem like a collection of "modules," each specializes in a specific mental feat. But just like in other domains of Nature, it is possible that much of the brain and mind's operation can be explained with a small set of universal principles. Given exciting recent developments in theory, empirical findings and computational studies, it seems that the generation of predictions might be one strong candidate for such a universal principle. This is the focus of Predictions in the brain. From the predictions required when a rat navigates a maze to food-caching in scrub-jays; from predictions essential in decision-making to social interactions; from predictions in the retina to the prefrontal cortex; and from predictions in early development to foresight in non-humans. The perspectives represented in this collection span a spectrum from the cellular underpinnings to the computational principles underlying future-related mental processes, and from systems neuroscience to cognition and emotion. In spite of this diversity, they share some core elements. Memory, for instance, is critical in any framework that explains predictions. In asking "what is next?" our brains have to refer to memory and experience on the way to simulating our mental future. But as much as this collection offers answers to important questions, it raises and emphasizes outstanding ones. How are experiences coded optimally to afford using them for predictions? How do we construct a new simulation from separate memories? How specific in detail are future-oriented thoughts, and when do they rely on imagery, concepts or language? Therefore, in addition to presenting the state-of-the-art of research and ideas about predictions as a universal principle in mind and brain, it is hoped that this collection will stimulate important new research into the foundations of our mental lives.
Download or read book ECEL2004 3rd European Conference on E Learning written by D. Remenyi and published by Academic Conferences Limited. This book was released on 2004-01-01 with total page 664 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Invariant Recognition of Visual Objects written by Evgeniy Bart and published by Frontiers E-books. This book was released on with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Research Topic will focus on how the visual system recognizes objects regardless of variations in the viewpoint, illumination, retinal size, background, etc. Contributors are encouraged to submit articles describing novel results, models, viewpoints, perspectives and/or methodological innovations relevant to this topic. The issues we wish to cover include, but are not limited to, perceptual invariance under one or more of the following types of image variation: • Object shape • Task • Viewpoint (from the translation and rotation of the object relative to the viewer) • Illumination, shading, and shadows • Degree of occlusion • Retinal size • Color • Surface texture • Visual context, including background clutter and crowding • Object motion (including biological motion). Examples of questions that are particularly interesting in this context include, but are not limited to: • Empirical characterizations of properties of invariance: does invariance always exist? How wide is its range and how strong is the tolerance to viewing conditions within this range? • Invariance in naïve vs. experienced subjects: Is invariance built-in or learned? How can it be learned, under which conditions and how effectively? Is it learned incidentally, or are specific task and reward structures necessary for learning? How is generalizability and transfer of learning related to the generalizability/invariance of perception? • Invariance during inference: Are there conditions (e.g. fast presentation time or otherwise resource-constrained recognition) when invariance breaks? • What are some plausible computational or neural mechanisms by which invariance could be achieved?
Download or read book Emergence Of Artificial Cognition The An Introduction To Collective Learning written by Peter Bock and published by World Scientific Publishing Company. This book was released on 1993-03-17 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this extraordinary new book, a pioneer in the research on Collective Learning Systems (an adaptive learning paradigm for artificial intelligence) describes the processes and mechanisms of human and artificial cognition, defines a fundamental building block for assembling large-scale adaptive systems (the learning cell) and proposes a design for the ultimate machine: a hierarchical network of 100 million learning cells that could exhibit the full range of cognitive capabilities of the human cerebral cortex.The author demonstrates that using the classical “expert system” approach to create such a vast knowledge base would require thousands of years to program all the necessary rules. He then explains how an adaptive Collective Learning System could achieve this goal in a matter of 20 years, much as humans do. Based on natural anatomical and behavioral precedents, Collective Learning enables a machine to learn the appropriate rules through trial-and-error interaction with the real world.In the course of explaining the principles of Collective Learning and his design for the ultimate machine, the author introduces a new theory of games for modelling the processes of the universe and discusses the philosophical issues raised by the prospect of creating machines that exhibit human-like intelligence. In addition to a number of small-scale software illustrations of Collective Learning, the final chapter presents the remarkable results of a large-scale research project directed by the author: a hardware and software simulation of the sub-symbolic image-processing functions of the primary visual cortex of the brain.To make the content palatable to a wide variety of readers, the book is written in a conversational style and laced with humor.Lengthy mathematical derivations and proofs have been omitted or abbreviated. Bibliographical references to scholarly journal papers and books are included to guide theoreticians to the attendant formalisms.
Download or read book Building Neural Networks written by David M. Skapura and published by Addison-Wesley Professional. This book was released on 1996 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organized by application areas, rather than by specific network architectures or learning algorithms, Building Neural Networks shows why certain networks are more suitable than others for solving specific kinds of problems. Skapura also reviews principles of neural information processing and furnishes an operations summary of the most popular neural-network processing models.
Download or read book Agent Oriented Programming written by Matthew M. Huntbach and published by Springer. This book was released on 2003-07-31 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: A book that furnishes no quotations is, me judice, no book – it is a plaything. TL Peacock: Crochet Castle The paradigm presented in this book is proposed as an agent programming language. The book charts the evolution of the language from Prolog to intelligent agents. To a large extent, intelligent agents rose to prominence in the mid-1990s because of the World Wide Web and an ill-structured network of multimedia information. Age- oriented programming was a natural progression from object-oriented programming which C++ and more recently Java popularized. Another strand of influence came from a revival of interest in robotics [Brooks, 1991a; 1991b]. The quintessence of an agent is an intelligent, willing slave. Speculation in the area of artificial slaves is far more ancient than twentieth century science fiction. One documented example is found in Aristotle’s Politics written in the fourth century BC. Aristotle classifies the slave as “an animate article of property”. He suggests that slaves or subordinates might not be necessary if “each instrument could do its own work at command or by anticipation like the statues of Daedalus and the tripods of Hephaestus”. Reference to the legendary robots devised by these mythological technocrats, the former an artificer who made wings for Icarus and the latter a blacksmith god, testify that the concept of robot, if not the name, was ancient even in Aristotle’s time.
Download or read book Human Face Recognition Using Third Order Synthetic Neural Networks written by Okechukwu A. Uwechue and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 132 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human Face Recognition Using Third-Order Synthetic Neural Networks explores the viability of the application of High-order synthetic neural network technology to transformation-invariant recognition of complex visual patterns. High-order networks require little training data (hence, short training times) and have been used to perform transformation-invariant recognition of relatively simple visual patterns, achieving very high recognition rates. The successful results of these methods provided inspiration to address more practical problems which have grayscale as opposed to binary patterns (e.g., alphanumeric characters, aircraft silhouettes) and are also more complex in nature as opposed to purely edge-extracted images - human face recognition is such a problem. Human Face Recognition Using Third-Order Synthetic Neural Networks serves as an excellent reference for researchers and professionals working on applying neural network technology to the recognition of complex visual patterns.
Download or read book Intelligent Biometric Techniques in Fingerprint and Face Recognition written by L.C. Jain and published by Routledge. This book was released on 2022-01-26 with total page 474 pages. Available in PDF, EPUB and Kindle. Book excerpt: The tremendous world-wide interest in intelligent biometric techniques in fingerprint and face recognition is fueled by the myriad of potential applications, including banking and security systems, and limited only by the imaginations of scientists and engineers. This growing interest poses new challenges to the fields of expert systems, neural networks, fuzzy systems, and evolutionary computing, which offer the advantages of learning abilities and human-like behavior. Authored by a panel of international experts, this book presents a thorough treatment of established and emerging applications and techniques relevant to this field.
Download or read book AIAA Computing in Aerospace Conference written by and published by . This book was released on with total page 852 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Advances in Pattern Recognition written by José Francisco Martinez-Trinidad and published by Springer Science & Business Media. This book was released on 2010-09-13 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed proceedings of the Second Mexican Conference on Pattern Recognition, MCPR 2010, held in Puebly, Mexico, in September 2010. The 39 revised papers were carefully reviewed and selected from 89 submissions and are organized in topical sections on computer vision and robotics, image processing, neural networks and signal processing, pattern recognition, data mining, natural language and document processing.
Download or read book Toward Category Level Object Recognition written by Jean Ponce and published by Springer. This book was released on 2007-01-25 with total page 622 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is a post-event proceedings volume and contains selected papers based on presentations given, and vivid discussions held, during two workshops held in Taormina in 2003 and 2004. The 30 thoroughly revised papers presented are organized in the following topical sections: recognition of specific objects, recognition of object categories, recognition of object categories with geometric relations, and joint recognition and segmentation.
Download or read book Computer Vision Metrics written by Scott Krig and published by Springer. This book was released on 2016-09-16 with total page 653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods and deep learning. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics and deep learning architectures. The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods. To complement the survey, the textbook includes useful analyses which provide insight into the goals of various methods, why they work, and how they may be optimized. The text delivers an essential survey and a valuable taxonomy, thus providing a key learning tool for students, researchers and engineers, to supplement the many effective hands-on resources and open source projects, such as OpenCV and other imaging and deep learning tools.
Download or read book Algorithmic Learning Theory written by Jyriki Kivinen and published by Springer Science & Business Media. This book was released on 2011-09-23 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models.
Download or read book Emerging Capabilities and Applications of Artificial Higher Order Neural Networks written by Zhang, Ming and published by IGI Global. This book was released on 2021-02-05 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.
