Criminology: Theories, Patterns, and Typologies: Edition 12

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The bestselling text on the market--now in its Twelfth Edition--CRIMINOLOGY: THEORIES, PATTERNS, AND TYPOLOGIES delivers the most comprehensive, in-depth analysis of criminological theory and crime typologies available. In addition to its unparalleled breadth and depth of coverage, the text is unrivaled in its strong research base and currency. The chapters in Part Three (Crime Typologies) focus on some of the hottest issues in the field today: green crime, transnational crime, and cybercrime. Packed with real-world illustrations, the Twelfth Edition is completely updated and includes cutting-edge seminal research, up-to-the-minute policy, newsworthy examples, and hundreds of new references. Renowned for his unbiased presentation of theories, issues, and controversies, Dr. Siegel encourages students to weigh the evidence and form their own conclusions.
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Publisher
Cengage Learning
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Published on
Jan 1, 2015
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Pages
640
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ISBN
9781305446090
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Language
English
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Genres
Education / Counseling / General
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Content Protection
This content is DRM protected.
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Learn the techniques for object recognition, 3D reconstruction, stereo imaging, and other computer vision applications using examples on different functions of OpenCV.Key Features Learn how to apply complex visual effects to images with OpenCV 3.x and Python Extract features from an image and use them to develop advanced applications Build algorithms to help you understand image content and perform visual searches Get to grips with advanced techniques in OpenCV such as machine learning, artificial neural network, 3D reconstruction, and augmented realityBook Description

Computer vision is found everywhere in modern technology. OpenCV for Python enables us to run computer vision algorithms in real time. With the advent of powerful machines, we have more processing power to work with. Using this technology, we can seamlessly integrate our computer vision applications into the cloud. Focusing on OpenCV 3.x and Python 3.6, this book will walk you through all the building blocks needed to build amazing computer vision applications with ease.

We start off by manipulating images using simple filtering and geometric transformations. We then discuss affine and projective transformations and see how we can use them to apply cool advanced manipulations to your photos like resizing them while keeping the content intact or smoothly removing undesired elements. We will then cover techniques of object tracking, body part recognition, and object recognition using advanced techniques of machine learning such as artificial neural network. 3D reconstruction and augmented reality techniques are also included. The book covers popular OpenCV libraries with the help of examples.

This book is a practical tutorial that covers various examples at different levels, teaching you about the different functions of OpenCV and their actual implementation. By the end of this book, you will have acquired the skills to use OpenCV and Python to develop real-world computer vision applications.

What you will learn Detect shapes and edges from images and videos How to apply filters on images and videos Use different techniques to manipulate and improve images Extract and manipulate particular parts of images and videos Track objects or colors from videos Recognize specific object or faces from images and videos How to create Augmented Reality applications Apply artificial neural networks and machine learning to improve object recognitionWho this book is for

This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors, matrices, and so on.

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