Top Vision books recommended by experts

At MentorCruise, we are all about making the most out of the experience of others. As part of that, we've connected and asked dozens of experts and professionals about their favourite Vision books – and here are the answers.

Table of Contents

Fundamentals of Vision

Understanding the concepts of Vision starts with understanding the fundamentals. On your way to mastery, it's crucial for you to understand how certain concepts were derived, and why things work like they do. Starting with these resources is the best way to do so.

Learning OpenCV: Computer Vision with the OpenCV

"This library is useful for practitioners, and is an excellent tool for those entering the field: it is a set of computer vision algorithms that work as advertised." -William T. Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology Learning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators …

Recommended by the experts and mentors at MentorCruise

Learning OpenCV 4 Computer Vision with Python 3: Get to Grips with Tools, Techniques, and Algorithms for Computer Vision and Machine Learning

Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 4 and Python 3. ...

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Computer Vision Metrics: Survey, Taxonomy, and Analysis

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. ...

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Computer vision

Computer Vision: Algorithms and Applications explores the variety of techniques commonly used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both for specialized applications such as medical imaging, and for fun, consumer-level tasks such as image editing and stitching, which students can apply to their own person…

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Modern Computer Vision with PyTorch: Explore Deep Learning Concepts and Implement Over 50 Real-world Image Applications

Get to grips with deep learning techniques for building image processing applications using PyTorch with the help of code notebooks and test questions ▶Book Description Deep learning is the driving force behind many recent advances in various computer vision (CV) applications. ...

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Learning TensorFlow

TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. It was developed by the Google Brain team for Google's internal use in research and production.

Recommended by the experts and mentors at MentorCruise

Additional Vision Reading

These books are not required for you to learn Vision, but they are highly recommended for you to deepen your knowledge.

Multiple view geometry in computer vision

A basic problem in computer vision is to understand the structure of a real world scene given several images of it. Techniques for solving this problem are taken from projective geometry and photogrammetry. ...

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Deep Learning for Vision Systems

How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. ...

Recommended by the experts and mentors at MentorCruise

Machine Learning Design Patterns

The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. ...

Recommended by the experts and mentors at MentorCruise

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Started my career in aerospace as a systems engineer before converting to product management at Google. Over my time at NASA, Google, Uber, and others I've built a successful toolkit of approaches to diverse and complicated product problems. I specialize in mentoring career transitions into product management and converting teams …

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