Gaussian Filter

analysis, coding and simulation

Much of this book is concerned with autoregressive and moving av­ erage linear stationary sequences and random fields. These models are part of the classical literature in time series analysis, particularly in the Gaussian case.

Computer Vision-Become an ace of Computer Vision, Computer Vision for Apps using Python, OpenCV, TensorFlow, etc.

Less theory but more code to build complex OpenCV applications

This book provides an overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields.

Learn Image Processing with Matlab

Adaptive filtering is a topic of immense practical and theoretical value, having applications in areas ranging from digital and wireless communications to biomedical systems. This book enables readers to gain a gradual and solid introduction to the subject, its applications to a variety of topical problems, existing limitations, and extensions of current theories. The book consists of eleven parts?each part containing a series of focused lectures and ending with bibliographic comments, problems, and computer projects with MATLAB solutions.

Online Introduction to Artificial Intelligence is based on Stanford CS221, Introduction to Artificial Intelligence. This class introduces students to the basics of Artificial Intelligence, which includes machine learning, probabilistic reasoning, robotics, and natural language processing. The objective of this class is to teach you modern AI. You learn about the basic techniques and tricks of the trade, at the same level we teach our Stanford students. We also aspire to excite you about the field of AI. Whether you are a seasoned professional, a college student, or a curious high school student - everyone can participate.