Computer Vision, Pattern Recognition, Image Processing, and Graphics, Rameshan
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 66520.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.
Автор: Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong Название: Mathematics for Machine Learning ISBN: 110845514X ISBN-13(EAN): 9781108455145 Издательство: Cambridge Academ Рейтинг: Цена: 42230.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This self-contained textbook introduces all the relevant mathematical concepts needed to understand and use machine learning methods, with a minimum of prerequisites. Topics include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics.
Автор: Henry Braun, Pavan Turaga, Andreas Spanias, Sameeksha Katoch, Suren Jayasuriya, Cihan Tepedelenlioglu Название: Reconstruction-Free Compressive Vision for Surveillance Applications ISBN: 1681735563 ISBN-13(EAN): 9781681735566 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 67450.00 T Наличие на складе: Нет в наличии. Описание: Compressed sensing (CS) allows signals and images to be reliably inferred from undersampled measurements. Exploiting CS allows the creation of new types of high-performance sensors including infrared cameras and magnetic resonance imaging systems. Advances in computer vision and deep learning have enabled new applications of automated systems. In this book, we introduce reconstruction-free compressive vision, where image processing and computer vision algorithms are embedded directly in the compressive domain, without the need for first reconstructing the measurements into images or video. Reconstruction of CS images is computationally expensive and adds to system complexity. Therefore, reconstruction-free compressive vision is an appealing alternative particularly for power-aware systems and bandwidth-limited applications that do not have on-board post-processing computational capabilities. Engineers must balance maintaining algorithm performance while minimizing both the number of measurements needed and the computational requirements of the algorithms. Our study explores the intersection of compressed sensing and computer vision, with the focus on applications in surveillance and autonomous navigation. Other applications are also discussed at the end and a comprehensive list of references including survey papers are given for further reading.
Автор: Milind G. Padalkar, Manjunath V. Joshi Название: Digital Heritage Reconstruction Using Super-resolution and Inpainting ISBN: 1627059210 ISBN-13(EAN): 9781627059213 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: Presents techniques to obtain higher resolution photographs of digitally reconstructed monuments. The resulting images can serve as input to immersive walkthrough systems. This book is a giant step toward ensuring that the iconic sites of our past are always available, and will never be truly lost.
Автор: Flach Название: Machine Learning ISBN: 1107422221 ISBN-13(EAN): 9781107422223 Издательство: Cambridge Academ Рейтинг: Цена: 50680.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, the book explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.
In the age of e-society, handwritten signature processing is an enabling technology in a multitude of fields in the "digital agenda" of many countries, ranging from e-health to e-commerce, from e-government to e-justice, from e-democracy to e-banking, and smart cities. Handwritten signatures are very complex signs; they are the result of an elaborate process that depends on the psychophysical state of the signer and the conditions under which the signature apposition process occurs. Notwithstanding, recent efforts from academies and industries now make possible the integration of signature-based technologies into other standard equipment to form complete solutions that are able to support the security requirements of today's society.
Advances in Digital Handwritten Signature Processing primarily provides an update on the most fascinating and valuable researches in the multifaceted field of handwritten signature analysis and processing. The chapters within also introduce and discuss critical aspects and precious opportunities related to the use of this technology, as well as highlight fundamental theoretical and applicative aspects of the field.
This book contains papers by well-recognized and active researchers and scientists, as well as by engineers and commercial managers working for large international companies in the field of signature-based systems for a wide range of applications and for the development of e-society.
This publication is devoted to both researchers and experts active in the field of biometrics and handwriting forensics, as well as professionals involved in the development of signature-based solutions for advanced applications in medicine, finance, commerce, banking, public and private administrations, etc. Handwritten Signature Processing may also be used as an advanced textbook by graduate students.
Автор: Tat-Jun Chin, David Suter Название: The Maximum Consensus Problem: Recent Algorithmic Advances ISBN: 1627052925 ISBN-13(EAN): 9781627052924 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 66530.00 T Наличие на складе: Невозможна поставка. Описание: The Maximum Consensus Problem refers to the problem of optimizing the quantity of interest according to the maximum consensus criterion. This book provides an overview of the algorithms for performing this optimization. The emphasis is on the basic operation or "inner workings" of the algorithms, and on their mathematical characteristics in terms of optimality and efficiency.
Автор: Kung Название: Kernel Methods and Machine Learning ISBN: 110702496X ISBN-13(EAN): 9781107024960 Издательство: Cambridge Academ Рейтинг: Цена: 90810.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Containing numerous algorithms and major theorems, this step-by-step guide covers the fundamentals of kernel-based learning theory. Including over two hundred problems and real-world examples, it is an essential resource for graduate students and professionals in computer science, electrical and biomedical engineering. Solutions to problems are provided online for instructors.
Автор: B B Chaudhuri Название: Advances in Digital Document Processing and Retrieval ISBN: 9814368709 ISBN-13(EAN): 9789814368704 Издательство: World Scientific Publishing Рейтинг: Цена: 118270.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Suitable for both students and researchers working on various aspects of document image analysis and recognition problems, this title covers such topics as: Going beyond the Myth of Paperlessness, The Role of Document Image Analysis in Trustworthy Elections as well as Word Recognition for Museum Index Cards with SNT-Grid.
Автор: Barfoot Timothy D Название: State Estimation for Robotics ISBN: 1107159393 ISBN-13(EAN): 9781107159396 Издательство: Cambridge Academ Рейтинг: Цена: 95030.00 T Наличие на складе: Невозможна поставка. Описание: This book is intended for students and practitioners of robotics who are interested in using noisy sensor data to estimate the position, orientation, and other state variables of robots as they move through the three-dimensional world. It covers classical and modern techniques commonly used in robotics today.
Автор: Babu R. Venkatesh, Prasanna Mahadeva, Namboodiri Vinay P. Название: Computer Vision, Pattern Recognition, Image Processing, and Graphics: 7th National Conference, Ncvpripg 2019, Hubballi, India, December 22-24, 2019, R ISBN: 9811586969 ISBN-13(EAN): 9789811586965 Издательство: Springer Цена: 83850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the 7th National Conference on Computer Vision, Pattern Recognition, Image Processing, and Graphics, NCVPRIPG 2019, held in Hubballi, India, in December 2019. The 55 revised full papers 3 short papers presented in this volume were carefully reviewed and selected from 210 submissions.
Автор: Diego Alexander et al Название: Pattern Recognition Applications in Engineering ISBN: 179981839X ISBN-13(EAN): 9781799818397 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 193110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The implementation of data and information analysis has become a trending solution within multiple professions. New tools and approaches are continually being developed within data analysis to further solve the challenges that come with professional strategy. Pattern recognition is an innovative method that provides comparison techniques and defines new characteristics within the information acquisition process. Despite its recent trend, a considerable amount of research regarding pattern recognition and its various strategies is lacking.
Pattern Recognition Applications in Engineering is an essential reference source that discusses various strategies of pattern recognition algorithms within industrial and research applications and provides examples of results in different professional areas including electronics, computation, and health monitoring. Featuring research on topics such as condition monitoring, data normalization, and bio-inspired developments, this book is ideally designed for analysts; researchers; civil, mechanical, and electronic engineers; computing scientists; chemists; academicians; and students.
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