Domain Adaptation in Computer Vision with Deep Learning, Venkateswara Hemanth, Panchanathan Sethuraman

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: Bradley Efron and Trevor Hastie
Название: Computer Age Statistical Inference
ISBN: 1107149894 ISBN-13(EAN): 9781107149892
Издательство: Cambridge Academ
Рейтинг:
Цена: 60190.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

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: Thanasis Daradoumis; Stavros N. Demetriadis; Fatos
Название: Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning
ISBN: 3642447686 ISBN-13(EAN): 9783642447686
Издательство: Springer
Рейтинг:
Цена: 121890.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book reviews and analyzes new implementation perspectives for intelligent adaptive learning and collaborative systems, enabled by advances in scripting languages, IMS LD, educational modeling languages and learning activity management systems.

Автор: Shanmugamani Rajalingappaa
Название: Deep Learning for Computer Vision
ISBN: 1788295625 ISBN-13(EAN): 9781788295628
Издательство: Неизвестно
Цена: 53940.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision, the science of manipulating and processing images. In this book, you will learn different techniques in deep learning to accomplish tasks related to object classification, object detection, image segmentation, captioning, ...

Автор: Koul Anirudh, Ganju Siddha, Kasam Meher
Название: Practical Deep Learning for Cloud and Mobile: Hands-On Computer Vision Projects Using Python, Keras & Tensorflow
ISBN: 149203486X ISBN-13(EAN): 9781492034865
Издательство: Wiley
Рейтинг:
Цена: 76020.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This step-by-step guide teaches you how to build practical deep learning applications for the cloud and mobile using a hands-on approach.

Автор: Kristin J. Dana
Название: Computational Texture and Patterns: From Textons to Deep Learning
ISBN: 1681730111 ISBN-13(EAN): 9781681730110
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 51750.00 T
Наличие на складе: Невозможна поставка.
Описание: Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn about the physical world. Our ability to capture visual imagery with cameras and sensors has resulted in vast amounts of raw data, but using this information effectively in a task-specific manner requires sophisticated computational representations. We enumerate specific desirable traits for these representations: (1) intraclass invariance—to support recognition; (2) illumination and geometric invariance for robustness to imaging conditions; (3) support for prediction and synthesis to use the model to infer continuation of the pattern; (4) support for change detection to detect anomalies and perturbations; and (5) support for physics-based interpretation to infer system properties from appearance. In recent years, computer vision has undergone a metamorphosis with classic algorithms adapting to new trends in deep learning. This text provides a tour of algorithm evolution including pattern recognition, segmentation and synthesis. We consider the general relevance and prominence of visual pattern analysis and applications that rely on computational models.

Автор: Le Lu; Yefeng Zheng; Gustavo Carneiro; Lin Yang
Название: Deep Learning and Convolutional Neural Networks for Medical Image Computing
ISBN: 3319827138 ISBN-13(EAN): 9783319827131
Издательство: Springer
Рейтинг:
Цена: 149060.00 T
Наличие на складе: Поставка под заказ.
Описание: This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.

Название: Deep Learning in Computer Vision
ISBN: 1138544426 ISBN-13(EAN): 9781138544420
Издательство: Taylor&Francis
Рейтинг:
Цена: 88800.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community.

Автор: Ranjan Sumit, Senthamilarasu S.
Название: Applied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques
ISBN: 1838646302 ISBN-13(EAN): 9781838646301
Издательство: Неизвестно
Рейтинг:
Цена: 60070.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book teaches you the different techniques and methodologies associated while implementing deep learning solutions in self-driving cars. You will use real-world examples to implement various neural network architectures to develop your own autonomous and automated vehicle using the Python environment.

Автор: Albena Dimitrova Mihovska, Roshani Raut
Название: Handbook of Research on the Impact of Deep Learning and IoT on Multi-Industry Applications
ISBN: 1799875113 ISBN-13(EAN): 9781799875116
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 260570.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings.

The Handbook of Research on the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers' points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.

Автор: Krig Scott
Название: Computer Vision Metrics: Survery, Taxonomy and Analysis of Computer Vision, Visual Neuroscience, and Deep Learning
ISBN: 3319815954 ISBN-13(EAN): 9783319815954
Издательство: Springer
Рейтинг:
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 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.