Computer Vision and Machine Intelligence Paradigms for SDGs, Kannan
Автор: Strang Gilbert Название: Linear Algebra and Learning from Data ISBN: 0692196382 ISBN-13(EAN): 9780692196380 Издательство: Cambridge Academ Рейтинг: Цена: 9978.00 р. 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: 6334.00 р. 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: Hamilton, William L. Название: Graph Representation Learning ISBN: 3031004604 ISBN-13(EAN): 9783031004605 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis.This book provides a synthesis and overview of graph representation learning.
Автор: Roberto Cipolla; Sebastiano Battiato; Giovanni Mar Название: Machine Learning for Computer Vision ISBN: 3642446868 ISBN-13(EAN): 9783642446863 Издательство: Springer Рейтинг: Цена: 16977.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Collecting articles covering talks and tutorials from the latest session of the International Computer Vision Summer School (ICVSS), this book offers a thorough exploration of current progress in the science and technology of making machines that see.
Автор: Marzena Kryszkiewicz; Sanghamitra Bandyopadhyay; H Название: Pattern Recognition and Machine Intelligence ISBN: 3319199404 ISBN-13(EAN): 9783319199405 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the proceedings of the 6th International Conference on Pattern Recognition and Machine Intelligence, PReMI 2015, held in Warsaw, Poland, in June/July 2015. The total of 53 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 90 submissions. They were organized in topical sections named: foundations of machine learning; image processing; image retrieval; image tracking; pattern recognition; data mining techniques for large scale data; fuzzy computing; rough sets; bioinformatics; and applications of artificial intelligence.
Автор: Enrico Vicario Название: Image Description and Retrieval ISBN: 1461371872 ISBN-13(EAN): 9781461371878 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Afterwards, different model- ing approaches are addressed in six chapters contributed by major research groups in the field: modeling based on object shape is addressed in chapter 2 by F.
Автор: Vipin Kumar; P.S. Gopalakrishnan; Laveen N. Kanal Название: Parallel Algorithms for Machine Intelligence and Vision ISBN: 1461279941 ISBN-13(EAN): 9781461279945 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent research results in the area of parallel algorithms for problem solving, search, natural language parsing, and computer vision, are brought together in this book.
Описание: Should we regulate artificial intelligence? Can we? From self-driving cars and high-speed trading to algorithmic decision-making, the way we live, work, and play is increasingly dependent on AI systems. This book examines how our laws are dealing with AI, as well as what additional rules and institutions are needed.
Автор: Jyotsna Kumar Mandal; Somnath Mukhopadhyay; Parama Название: Algorithms in Machine Learning Paradigms ISBN: 9811510407 ISBN-13(EAN): 9789811510403 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Chapter 1. Development of Trapezoidal Hesitant-Intuitionistic Fuzzy Prioritized Operators based on Einstein Operations with their Application to Multi-Criteria Group Decision Making.- Chapter 2. Graph-based Information-Theoretic Approach for Unsupervised Feature Selection.- Chapter 3. Fact based Expert System for supplier selection with ERP data.- Chapter 4. Handling Seasonal Pattern and Prediction using Fuzzy Time Series Model.- Chapter 5. Automatic Classification of Fruits and Vegetables: A Texture-based Approach.- Chapter 6. Deep Learning based Early Sign Detection Model for Proliferative Diabetic Retinopathy in Neovascularization at the Disc.- Chapter 7. A Linear Regression Based Resource Utilization Prediction Policy For Live Migration in Cloud Computing.- Chapter 8. Tracking changing human emotions from facial image sequence by landmark triangulation: A incircle-circumcircle duo approach.- Chapter 9. Recognizing Human Emotions from Facial Images by Landmark Triangulation: A Combined Circumcenter-Incenter-Centroid Trio Feature Based Method.- Chapter 10. Stable neighbor nodes prediction with multivariate analysis in mobile ad hoc network using RNN model.- Chapter 11. A New Approach for Optimizing Initial Parameters of Lorenz Attractor and its application in PRNG.
Автор: Popkova Elena G., Ostrovskaya Victoria N. Название: Meta-Scientific Study of Artificial Intelligence ISBN: 1648025153 ISBN-13(EAN): 9781648025150 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 17620.00 р. Наличие на складе: Нет в наличии.
Описание:
The book studies artificial intelligence as a new reality and a perspective direction for the modern economy's development, as well as its future technological basis. The book forms a meta-scientific approach to studying AI, which allows uniting the efforts of scholars from different spheres of science for formation of a comprehensive idea of AI. The book reflects the meta-scientific approach to the balanced use of human and artificial intelligence and the features of successful development of the information economy under the conditions of technological progress based on artificial intelligence. It describes the implementation of the subject approach in psychology and pedagogy based on artificial intelligence and reflects the political and legal aspects of creating, implementing and developing artificial intelligence. The impact of artificial intelligence on the economy and financial services is considered, and modernization of management of production and distribution processes and systems based on AI are studied. The target audience of the book includes scholars from different spheres of science who study AI, companies interested in implementation of AI, and government that regulates the issues of development and use of AI.
Описание: This book constitutes refereed proceedings of the 4th International Conference on Recent Trends in Advanced Computing - Computer Vision and Machine Intelligence Paradigms for Sustainable Development Goals. This book covers novel and state-of-the-art methods in computer vision coupled with intelligent techniques including machine learning, deep learning, and soft computing techniques. The contents of this book will be useful to researchers from industry and academia. This book includes contemporary innovations, trends, and concerns in computer vision with recommended solutions to real-world problems adhering to sustainable development from researchers across industry and academia. This book serves as a valuable reference resource for academics and researchers across the globe.
Development in any country is impossible if reliable and affordable energy, safe water and sanitation, as well as telecommunication facilities, are not easily accessible. Artificial intelligence and machine learning techniques are now widely used in all branches of engineering to build and optimize systems. The combination of AI and engineering can indeed act as a real catalyst to achieve the UN SDGs.
The volume editors present an analysis of different concepts and case studies in engineering disciplines such as chemical, civil, electrical, telecommunications and mechanical engineering, demonstrating how engineering systems and processes can leverage the power of AI to drive and achieve the UN SDGs. Topics covered include sustainable crop production and consumption, AI based clean water and sanitation monitoring, intelligent transport systems and achieving affordable and clean energy through AI and 5G powered internet of energy.
Such a study is of paramount importance and is a valuable source of information for researchers, engineers, and policy makers to be able to better design and adopt AI enabled techniques in different engineering areas, with a view to catalyze the achievement of the UN SDGs.
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