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This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data preprocessing, model design, model training, evaluation, deployment, and interpretability. Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras. You'll learn how to: Design ML architecture for computer vision tasks Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model Preprocess images for data augmentation and to support learnability Incorporate explainability and responsible AI best practices Deploy image models as web services or on edge devices Monitor and manage ML models
APlusPhysics: Your Guide to Regents Physics Essentials is a clear and concise roadmap to the entire New York State Regents Physics curriculum, preparing students for success in their high school physics class as well as review for high marks on the Regents Physics Exam. Topics covered include pre-requisite math and trigonometry; kinematics; forces; Newton's Laws of Motion, circular motion and gravity; impulse and momentum; work, energy, and power; electrostatics; electric circuits; magnetism; waves; optics; and modern physics. Featuring more than five hundred questions from past Regents exams with worked out solutions and detailed illustrations, this book is integrated with the APlusPhysics.com website, which includes online question and answer forums, videos, animations, and supplemental problems to help you master Regents Physics essentials. "The best physics books are the ones kids will actually read." Advance Praise for APlusPhysics Regents Physics Essentials: "Very well written... simple, clear engaging and accessible. You hit a grand slam with this review book." -- Anthony, NY Regents Physics Teacher. "Does a great job giving students what they need to know. The value provided is amazing." -- Tom, NY Regents Physics Teacher. "This was tremendous preparation for my physics test. I love the detailed problem solutions." -- Jenny, NY Regents Physics Student. "Regents Physics Essentials has all the information you could ever need and is much easier to understand than many other textbooks... it is an excellent review tool and is truly written for students." -- Cat, NY Regents Physics Student
This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).