Image Machine

This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with sel

This book introduces Raspberry Pi, using real world applications in computer vision, machine learning, and deep learning. It provides a detailed, step-by-step, approach to application development for

This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, includ

Image Quality Assessment is well-known for measuring the perceived image degradation of natural scene images but is still an emerging topic for computer-generated images. This book addresses this prob

When a machine boy falls to earth, his heart is awoken for the first time. As he learns to be human, he struggles to override his own programming and become a hero, from rising stars Tri Vuong and Irma Kniivila. It's a bird, it's a plane, it's... Machine Boy! When Machine Boy falls from the sky into the domed city of Mega 416, he leaves a wake of destruction in his path... until Karate Grandpa is able to turn on his heart. Now, Machine Boy wants nothing more than to become a hero! Whether he is fighting giant bugs in the school's basement, rescuing cats from trees, or making the perfect spaghetti sauce, Machine Boy is always looking for the best way to help others. But when his heart begins to interact dangerously with other debris from space, Machine Boy wonders if he can be a power for good after all. Rising stars Tri Vuong and Irma Kniivila create a funny and engaging all-ages adventure that asks-can you override your own programming?

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

A new, cataclysmic chapter of theDescender saga is here! All the various factions who have been hunting Tim-21finally converge around the ocean planet, Mata just as the robots launch theirgalaxy wide

This 2004 book is an accessible and comprehensive introduction to machine vision. It provides all the necessary theoretical tools and shows how they are applied in actual image processing and machine vision systems. A key feature is the inclusion of many programming exercises that give insights into the development of practical image processing algorithms. The authors begin with a review of mathematical principles and go on to discuss key issues in image processing such as the description and characterization of images, edge detection, restoration and feature extraction, segmentation, texture and shape. They also discuss image matching, statistical pattern recognition, clustering, and syntactic pattern recognition. Important applications are described, including optical character recognition and automatic target recognition. Software and data used in the book can be found at www.cambridge.org/9780521830461. A useful reference for practitioners, the book is aimed at graduate students in