Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
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Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
Develop strong grip on the fundamentals of Image Processing and Image Manipulation.
Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
Nº de artículo: 88901948

Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy,

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Nº de artículo: 88901948

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What Stands Out

Comprehensive Coverage
Offers over 50 solutions and techniques specifically for complex digital image processing challenges. Tailored for both beginners and advanced users aiming to enhance their skills with practical applications.
Expert Guidance
Utilizes popular libraries like Numpy, Scipy, Pytorch, and Keras, ensuring learners benefit from industry-standard practices. Designed by experts, it provides deep insights tailored for real-world applications.
Hands-On Approach
Emphasizes practical learning through step-by-step solutions, making it easy for users to implement concepts immediately, thereby bridging the gap between theory and real-world implementation in image processing.

Detalles de producto

Image Processing Masterclass with Python: 50+ Solutions and Techniques Solving Complex Digital Image Processing Challenges Using Numpy, Scipy, Pytorch and Keras (English Edition)
  • Over 50 problems solved with classical algorithms + ML / DL modelsKey Features Problem-driven approach to practice image processing. Practical usage of popular Python libraries: Numpy, Scipy, scikit-image, PIL and SimpleITK. End-to-end demonstration of popular facial image processing challenges using MTCNN and Microsoft’s Cognitive Vision APIs.DescriptionThis book starts with basic Image Processing and manipulation problems and demonstrates how to solve them with popular Python libraries and modules. It then concentrates on problems based on Geometric image transformations and problems to be solved with Image hashing. Next, the book focuses on solving problems based on Sampling, Convolution, Discrete Fourier transform, Frequency domain filtering and image restoration with deconvolution. It also aims at solving Image enhancement problems using different algorithms such as spatial filters and create a super resolution image using SRGAN.Finally, it explores popular facial image processing problems and solves them with Machine learning and Deep learning models using popular python ML / DL libraries.What you will learn Develop strong grip on the fundamentals of Image Processing and Image Manipulation. Solve popular Image Processing problems using Machine Learning and Deep Learning models. Working knowledge on Python libraries including numpy, scipy and scikit-image. Use popular Python Machine Learning packages such as scikit-learn, Keras and pytorch. Live implementation of Facial Image Processing techniques such as Face Detection / Recognition / Parsing dlib and MTCNN.Who this book is forThis book is designed specially for computer vision users, machine learning engineers, image processing experts who are looking for solving modern image processing/computer vision challenges.Table of Contents1. Chapter 1: Basic Image & Video Processing2. Chapter 2: More Image Transformation and Manipulation3. Chapter 3: Sampling, Convolution and Discrete Fourier Transform4. Chapter 4: Discrete Cosine / Wavelet Transform and Deconvolution5. Chapter 5: Image Enhancement6. Chapter 6: More Image Enhancement7. Chapter 7: Face Image ProcessingAbout the Author 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, such as 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 also authored a couple of Image Processing books, published from an international publication house. He has earned certifications from 100+ MOOCs on data science and related courses. He is a regular blogger (at sandipanweb @wordpress, medium and data science central) and is a Machine Learning education enthusiast. LinkedIn Profile: https://www.linkedin.com/in/sandipan-dey-0370276
Publisher BPB Publications
Publication date March 10, 2021
Language English
Print length 428 pages
ISBN-10 9389898641
ISBN-13 978-9389898644
Item Weight 1.63 pounds (740 grams)
Dimensions 7.5 x 0.97 x 9.25 inches (19.1 x 2.5 x 23.5 cm)

Who Should Buy?

Suitable For
  • Aspiring Developers

    Individuals eager to learn digital image processing techniques using Python libraries like Numpy and Pytorch.

  • Data Science Enthusiasts

    Those interested in enhancing their skills in data analysis and machine learning through practical image processing applications.

  • Academics and Researchers

    Students or professionals conducting research that involves advanced image processing challenges in their projects or studies.

Not Suitable For
  • Beginners in Python

    Complete newcomers to Python programming may find the content too advanced without foundational knowledge.

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ventajas

  • Comprehensive coverage of topics
  • Hands-on practical exercises
  • Clear explanations and examples
  • Suitable for all skill levels
  • Real-world applications discussed

Contras

  • Some sections could use more depth.

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características y beneficios

  • Over 50 image processing problems are addressed with classical algorithms and ML/DL models.
  • Practical usage of popular Python libraries like Numpy, Scipy, and scikit-image.
  • Comprehensive coverage of facial image processing techniques using deep learning.
  • Hands-on approach to solving geometric transformations and image enhancement.
  • Ideal for computer vision users, machine learning engineers, and image processing experts.
  • End-to-end solutions for modern image processing challenges.

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