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Название: Generalization with Deep Learning: For Improvement on Sensing Capability
Автор: Zhenghua Chen, Min Wu, Xiaoli Li
Издательство: World Scientific Publishing Company
Год: 2021
Формат: true pdf, epub
Страниц: 324
Размер: 10 Mb, 16.5 Mb
Язык: English

Deep Learning has achieved great success in many challenging research areas, such as image recognition and natural language processing. The key merit of deep learning is to automatically learn good feature representation from massive data conceptually. In this book, we will show that the deep learning technology can be a very good candidate for improving sensing capabilities.

Название: Applied User Data Collection and Analysis Using jаvascript and PHP
Автор: Kyle Goslin, Markus Hofmann
Издательство: CRC Press
Год: 2021
Формат: True PDF
Страниц: 346
Размер: 10 Mb
Язык: English

Applied User Data Collection and Analysis Using jаvascript and PHP is designed to provide the technical skills and competency to gather a wide range of user data from web applications in both active and passive methods. This is done by providing the reader with real-world examples of how a variety of different jаvascript- and PHP-based libraries can be used to gather data using custom feedback forms and embedded data gathering tools.

Название: Vision, Sensing and Analytics: Integrative Approaches
Автор: Md Atiqur Rahman Ahad, Atsushi Inoue
Издательство: Springer
Год: 2021
Страниц: 416
Язык: английский
Формат: pdf (true), epub
Размер: 49.0 MB

This book serves as the first guideline of the integrative approach, optimal for our new and young generations. Recent technology advancements in computer vision, IoT sensors, and analytics open the door to highly impactful innovations and applications as a result of effective and efficient integration of those. Such integration has brought to scientists and engineers a new approach - the integrative approach. This offers far more rapid development and scalable architecting when comparing to the traditional hardcore developmental approach. Computer vision has advanced so far that machines now can think and see as we humans do. Especially Deep Learning (DL) has raised the bar of excellence in computer vision. However, the recent emergence of deep reinforcement learning is threatening to soar even greater heights as it combines deep neural networks with reinforcement learning along with numerous added advantages over both.

Название: Competitive Programming in Python :128 Algorithms to Develop your Coding Skills
Автор: Christoph Durr
Издательство: Cambridge University Press
Год: 2021
Формат: True PDF
Страниц: 266
Размер: 16 Mb
Язык: English

Want to kill it at your job interview in the tech industry? Want to win that coding competition? Learn all the algorithmic techniques and programming skills you need from two experienced coaches, problem setters, and jurors for coding competitions. The authors highlight the versatility of each algorithm by considering a variety of problems and show how to implement algorithms in simple and efficient code. Readers can expect to master 128 algorithms in Python and discover the right way to tackle a problem and quickly implement a solution of low complexity.

Название: Программное обеспечение матричных алгоритмов и метода конечных элементов в инженерных расчетах
Автор: Бурман З.И., Артюхин Г.А., Зархин Б.Я.
Издательство: Машиностроение
Год: 1988
ISBN: 5-217-00011-2
Формат: pdf
Страниц: 256
Размер: 11 Мб
Язык: русский

Изложена методология создания программного обеспечения для численной реализации на ЭВМ матричных алгоритмов решения разнообразных задач механики и физики и, в частности, матричных алгоритмов метода конечных элементов.

Название: C# Features Succinctly
Автор: Dirk Strauss
Издательство: Syncfusion, Inc
Год: 2021
Формат: ePUB, PDF
Страниц: 77
Размер: 10 Mb
Язык: English

C# Features Succinctly is a concise guide to the significant features packaged in C# 7, 8, and 9. To help readers understand the evolution of the language, author Dirk Strauss first covers the important additions that arrived in version 7, such as tuples, pattern matching, and out variables. Next, he covers more than a dozen features in version 8, from nullable reference types to unmanaged constructed types. Finally, readers get a taste of the latest features in C# 9, and some of the productivity enhancements provided to .NET developers in Visual Studio.

Название: Artificial Intelligence (AI): Recent Trends and Applications
Автор: S. Kanimozhi Suguna, M. Dhivya, Sara Paiva
Издательство: CRC Press
Серия: Artificial Intelligence (AI): Elementary to Advanced Practices
Год: 2021
Страниц: 331
Язык: английский
Формат: pdf (true)
Размер: 26.6 MB

This book aims to bring together leading academic scientists, researchers, and research scholars to exchange and share their experiences and research results on all aspects of Artificial Intelligence. The book provides a premier interdisciplinary platform to present practical challenges and adopted solutions. The book addresses the complete functional framework workflow in Artificial Intelligence technology. It explores the basic and high-level concepts and can serve as a manual for the industry for beginners and the more advanced. It covers intelligent and automated systems and its implications to the real-world, and offers data acquisition and case studies related to data-intensive technologies in AI-based applications.

Название: Deep Learning for Biomedical Applications
Автор: Utku Kose, Omer Deperlioglu
Издательство: CRC Press
Год: 2021
Страниц: 365
Язык: английский
Формат: pdf (true)
Размер: 21.77 MB

This book is a detailed reference on biomedical applications using Deep Learning. Because Deep Learning is an important actor shaping the future of Artificial Intelligence, its specific and innovative solutions for both medical and biomedical are very critical. This book provides a recent view of research works on essential, and　advanced topics. The book offers detailed information on the application of Deep Learning for solving biomedical problems. It focuses on different types of data (i.e. raw data, signal-time series, medical images) to enable readers to understand the effectiveness and the potential. It includes topics such as disease diagnosis,　image processing perspectives, and even　genomics. It takes the reader through different sides of Deep Learning oriented solutions.

Название: Blockchain And Smart Contracts: Design Thinking And Programming For Fintech
Автор: Swee Won Lo, Yu Wang, David Lee Kuo Chuen
Издательство: World Scientific
Год: 2021
Страниц: 381
Язык: английский
Формат: pdf (true)
Размер: 45.9 MB

Innovative as it is, the blockchain technology is getting more and more attention and an increasing number of applications have emerged. This book elaborates on both the design thinking ideas and technical details in blockchain and smart contracts to help readers delve into the conceptual framework and understand why blockchain is designed as such and how it makes the current system decentralised yet effective. Having this understanding lays the ground for further analysis of blockchain-based solutions and innovative fintech applications. Topics covered in this book include blockchain structure, blockchain ecosystem, design thinking for blockchain, smart contract, fintech and financial services, solution-based problem solving, fintech valuation, and current issues faced such as privacy protection and solution selection, with the aid of real-life examples and hands-on exercises.

Название: Deep Neural Networks for Multimodal Imaging and Biomedical Applications
Автор: Annamalai Suresh, R. Udendhran, S. Vimal
Издательство: IGI Global
Год: 2020
Страниц: 310
Язык: английский
Формат: pdf (true)
Размер: 11.8 MB

The field of healthcare is seeing a rapid expansion of technological advancement within current medical practices. The implementation of technologies including neural networks, multi-model imaging, genetic algorithms, and soft computing are assisting in predicting and identifying diseases, diagnosing cancer, and the examination of cells. Implementing these biomedical technologies remains a challenge for hospitals worldwide, creating a need for research on the specific applications of these computational techniques. Deep Neural Networks for Multimodal Imaging and Biomedical Applications provides research exploring the theoretical and practical aspects of emerging data computing methods and imaging techniques within healthcare and biomedicine. The publication provides a complete set of information in a single module starting from developing deep neural networks to predicting disease by employing multi-modal imaging.