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Guide to Ambient Intelligence in the IoT Environment: Principles, Technologies and Applications (Computer Communications and Networks)
Guide to Ambient Intelligence in the IoT Environment: Principles, Technologies and Applications (Computer Communications and Networks)
Ambient intelligence (AmI) is an element of pervasive computing that brings smartness to living and business environments to make them more sensitive, adaptive, autonomous and personalized to human needs. It refers to intelligent interfaces that recognise human presence and preferences, and adjust smart environments to suit their...
Industrial Sensors and Controls in Communication Networks: From Wired Technologies to Cloud Computing and the Internet of Things (Computer Communications and Networks)
Industrial Sensors and Controls in Communication Networks: From Wired Technologies to Cloud Computing and the Internet of Things (Computer Communications and Networks)

This informative text/reference presents a detailed review of the state of the art in industrial sensor and control networks. The book examines a broad range of applications, along with their design objectives and technical challenges. The coverage includes fieldbus technologies, wireless communication technologies, network...

Computational Models of Reading: A Handbook (OXFORD SERIES ON COGNITIVE MODELS)
Computational Models of Reading: A Handbook (OXFORD SERIES ON COGNITIVE MODELS)
This book is about computational models of reading, or models that explain (and often simulate) the mental processes that allow us to convert the marks on a printed page into the representations that allow us to understand the contents of what we are reading. Computational Models of Reading
assumes no prior knowledge of the
...
Computational Methods for Deep Learning: Theoretic, Practice and Applications (Texts in Computer Science)
Computational Methods for Deep Learning: Theoretic, Practice and Applications (Texts in Computer Science)

Integrating concepts from deep learning, machine learning, and artificial neural networks, this highly unique textbook presents content progressively from easy to more complex, orienting its content about knowledge transfer from the viewpoint of machine intelligence. It adopts the methodology from graphical theory, mathematical...

High Dynamic Range Imaging, Second Edition: Acquisition, Display, and Image-Based Lighting
High Dynamic Range Imaging, Second Edition: Acquisition, Display, and Image-Based Lighting

This landmark book is the first to describe HDRI technology in its entirety and covers a wide-range of topics, from capture devices to tone reproduction and image-based lighting. The techniques described enable you to produce images that have a dynamic range much closer to that found in the real world, leading to an unparalleled visual...

Robust Statistics: Theory and Methods (Probability and Statistics)
Robust Statistics: Theory and Methods (Probability and Statistics)
Classical statistical techniques fail to cope well with deviations from a standard distribution. Robust statistical methods take into account these deviations while estimating the parameters of parametric models, thus increasing the accuracy of the inference. Research into robust methods is flourishing, with new methods being developed and...
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition
Python Deep Learning: Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow, 2nd Edition

Learn advanced state-of-the-art deep learning techniques and their applications using popular Python libraries

Key Features

  • Build a strong foundation in neural networks and deep learning with Python libraries
  • Explore advanced deep learning techniques and their applications...
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras
Deep Learning for Computer Vision: Expert techniques to train advanced neural networks using TensorFlow and Keras

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks

Key Features

  • Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision
  • Combine the power of Python, Keras, and TensorFlow to...
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach

This extraordinary book gives a uniquely modern view of computer vision. Offering a general survey of the whole computer vision enterprise along with sufficient detail for readers to be able to build useful applications, this book is invaluable in providing a strategic overview of computer vision. With extensive use of probabalistic...

An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics)
An Invitation to 3-D Vision: From Images to Geometric Models (Interdisciplinary Applied Mathematics)
This book is intended to give students at the advanced undergraduate or introductory graduate level, and researchers in computer vision, robotics and computer graphics, a self-contained introduction to the geometry of three-dimensional (3- D) vision. This is the study of the reconstruction of 3-D models of objects from a...
Feature Extraction & Image Processing, Second Edition
Feature Extraction & Image Processing, Second Edition
We will no doubt be asked many times: why on earth write a new book on computer vision? Fair question: there are already many good books on computer vision in the bookshops, as you will find referenced later, so why add to them? Part of the answer is that any textbook is a snapshot of material that exists before it. Computer vision, the art of...
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition
Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python, 2nd Edition

Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow.

Key Features

  • Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow
  • Explore deep neural...
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