Sandipan Dey - Python Image Processing Cookbook

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Sandipan Dey is a data scientist with a wide range of interests, covering topics such as machine learning, deep learning, image processing, and computer vision. He has worked in numerous data science fields, working with recommender systems, predictive models for the events industry, sensor localization models, sentiment analysis, and device prognostics. He earned his master's degree in computer science from the University of Maryland, Baltimore County, and has published in a few IEEE data mining conferences and journals. He has earned certifications from 100+ MOOCs on data science, machine learning, deep learning, image processing, and related courses. He is a regular blogger (sandipanweb) and is a machine learning education enthusiast.

Srinjoy Ganguly holds a master's in Artificial Intelligence from the University of Southampton, UK and has over 4 years of experience in AI. He completed his bachelor's in Electronics and Communications from GGSIPU, Delhi, and gained a thorough knowledge of signal processing algorithms and neural networks. He has actively pursued the theory and principles of machine learning, deep learning, computer vision, and reinforcement learning. His research interests include Bayesian machine learning, Bayesian deep learning, and quantum machine learning. He is also an active contributor to Julia language. He strongly believes that this book will be an extremely valuable asset into the hands of beginners in the field of AI and computer vision.

Shankar Jha is a software engineer who has helped a lot of beginners get to grips with Python through his articles and talks. He writes about Python, Django, tackling climate change, and poverty alleviation. He lives by the philosophy of Richard Feynman and Swami Vivekananda. His latest endeavor is to help facilitate the use of environment-friendly products. He believes this book will give you enough hands-on experience to jump start your career in computer vision.

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With advancements in wireless devices and mobile technology, there's an increasing demand for digital image processing skills to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of tools and algorithms, along with guiding you through analysis and visualization for image processing.

With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as image detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning-based techniques such as transfer learning and fine-tuning to solve real-world problems.

By the end of this Python book, you'll be proficient in applying image processing techniques effectively to leverage the capabilities of the Python ecosystem.