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Can I read Image Processing and Machine Learning, Volume 2 : Advanced Topics in Image Analysis and Machine Learning on EtoBox?

Image Processing and Machine Learning, Volume 2 : Advanced Topics in Image Analysis and Machine Learning by Erik Cuevas, Alma Nayeli Rodríguez is a nonfiction available to read on EtoBox.

What is Image Processing and Machine Learning, Volume 2 : Advanced Topics in Image Analysis and Machine Learning about?

Image processing and machine learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, machine learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches.Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important machine learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1.Written with instructors and students of image processing in mind, this book's intuitive organization also contains appeal for a

Who reads Image Processing and Machine Learning, Volume 2 : Advanced Topics in Image Analysis and Machine Learning?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Erik Cuevas, Alma Nayeli Rodríguez
Publisher
CRC Press LLC
Published
2024
Language
EN
ISBN
9781003829140
Category
nonfiction
Subjects
Science, Computer Science, Business

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