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Hands-On Image Processing with Python. Advanced methods for analyzing, transforming, and interpreting digital images - Second Edition Sandipan Dey

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Hands-On Image Processing with Python. Advanced methods for analyzing, transforming, and interpreting digital images - Second Edition Sandipan Dey - okladka książki

Hands-On Image Processing with Python. Advanced methods for analyzing, transforming, and interpreting digital images - Second Edition Sandipan Dey - okladka książki

Autor:
Sandipan Dey
Serie wydawnicze:
Learning
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Being able to process, extract information, and understand an image quickly has become a critical part of real-world applications within security, payment, healthcare, advertising, and other sectors. This book covers a wide range of topics, following a highly practical approach that takes you through a set of image processing concepts and algorithms to help you learn how to use leading Python library functions to implement these algorithms.

As you progress, you’ll gain proficiency in writing code snippets in Python 3 and quickly implement complex image processing and computer vision algorithms to solve problems in image enhancement, restoration, denoising, segmentation, classification, object detection and more, using image processing libraries such as PIL, scikit-mage, scipy ndimage, and opencv-python. You’ll also learn how to use ML models using scikit-learn and explore recent advances with deep learning models with CNNs (e.g., ResNet, Yolo) using tensorflow, keras, and pytorch. The final set of chapters will help you solve advanced problems, such as image-to-image translation, anisotropic diffusion, and generative arts.

By the end of this book, you will be well versed in image processing and ready to solve a variety of commonly occurring problems.

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O autorze książki

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.

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