A beginner-friendly guide to algorithmic trading covering market basics, strategy design and backtesting, risk management, and how to build simple Python trading bots, with no prior trading or coding experience requiredKey FeaturesLearn through a step-by-step, beginner-safe path from market fundamentals to a working automated trading botGain hands-on Python experience focused on realistic strategies, robustness, and risk managementLearn backtes...

Deep learning is making waves. At the time of this writing (March 2016), Google’s AlghaGo program just beat 9-dan professional Go player Lee Sedol at the game of Go, a Chinese board game. Experts in the field of Artificial Intelligence thought we were 10 years away from achieving a victory against a top professional Go player, but progress seems to have accelerated! While deep learning is a complex subject, it is not any more difficult to learn than any other machine learni...

Augmented Reality (AR) blurs the boundary between the physical and digital worlds. In AR’s current exploration phase, innovators are beginning to create compelling and contextually rich applications that enhance a user’s everyday experiences. In this book, Dr. Helen Papagiannis—a world-leading expert in the field—introduces you to AR: how it’s evolving, where the opportunities are, and where it’s headed.If you’re a designer, developer, entrepreneur, student, educator, business lead...

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and mo...

Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guideKey Features- Practical recipes on training different neural network models and tuning them for optimal performance-Use Python frameworks like TensorFlow, Caffe, Keras, Theano for Natural Language Processing, Computer Vision, and more-A hands-on guide covering the common as well as the not so common problems in deep learning u...

This book constitutes the thoroughly refereed post-conference proceedings of the Second International Workshop on Computer Assisted and Robotic Endoscopy, CARE 2015, held in conjunction with MICCAI 2015, in Munich, Germany, in October 2015.The 15 revised full papers were carefully selected out of 20 initial submissions and focus on recent technical advances associated with computer vision; graphics; robotics and medical imaging; external tracking systems; medical device control sys...

A practical guide to understanding the core machine learning and deep learning algorithms, and implementing them to create intelligent image processing systems using OpenCV 4Key FeaturesGain insights into machine learning algorithms, and implement them using OpenCV 4 and scikit-learnGet up to speed with Intel OpenVINO and its integration with OpenCV 4Implement high-performance machine learning models with helpful tips and best practices

Expand your knowledge of computer vision by building amazing projects with OpenCV Key FeaturesBook DescriptionComputer vision is becoming accessible to a large audience of software developers who can leverage mature libraries such as OpenCV. However, as they move beyond their first experiments in computer vision, developers may struggle to ensure that their solutions are sufficiently well optimized, well trained, robust, and adaptive in real-world cond...

Rapid development of computer hardware has enabled usage of automatic object recognition in an increasing number of applications, ranging from industrial image processing to medical applications, as well as tasks triggered by the widespread use of the internet. Each area of application has its specific requirements, and consequently these cannot all be tackled appropriately by a single, general-purpose algorithm. This easy-to-read text/reference provides a comprehensive introduction to the...

Image Processing and Pattern Recognition covers major applications in the field, including optical character recognition, speech classification, medical imaging, paper currency recognition, classification reliability techniques, and sensor technology. The text emphasizes algorithms and architectures for achieving practical and effective systems, and presents many examples. Practitioners, researchers, and students in computer science, electrical engineering, andradiology, as well as those w...

Written by leading researchers, the 2nd Edition of the Dictionary of Computer Vision & Image Processing is a comprehensive and reliable resource which now provides explanations of over 3500 of the most commonly used terms across image processing, computer vision and related fields including machine vision. It offers clear and concise definitions with short examples or mathematical precision where necessary for clarity that ultimately makes it a very usable reference for new entran...

Discrete-Time Neural Observers: Analysis and Applications presents recent advances in the theory of neural state estimation for discrete-time unknown nonlinear systems with multiple inputs and outputs. The book includes rigorous mathematical analyses, based on the Lyapunov approach, that guarantee their properties. In addition, for each chapter, simulation results are included to verify the successful performance of the corresponding proposed schemes. In order to complete the treatment of ...