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Bag of Words Model - Unlocking Visual Intelligence with Bag of Words - cover

Bag of Words Model - Unlocking Visual Intelligence with Bag of Words

Fouad Sabry

Publisher: One Billion Knowledgeable

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Summary

What is Bag of Words Model
 
In computer vision, the bag-of-words model sometimes called bag-of-visual-words model can be applied to image classification or retrieval, by treating image features as words. In document classification, a bag of words is a sparse vector of occurrence counts of words; that is, a sparse histogram over the vocabulary. In computer vision, a bag of visual words is a vector of occurrence counts of a vocabulary of local image features.
 
How you will benefit
 
(I) Insights, and validations about the following topics:
 
Chapter 1: Bag-of-words model in computer vision
 
Chapter 2: Image segmentation
 
Chapter 3: Scale-invariant feature transform
 
Chapter 4: Scale space
 
Chapter 5: Automatic image annotation
 
Chapter 6: Structure from motion
 
Chapter 7: Sub-pixel resolution
 
Chapter 8: Mean shift
 
Chapter 9: Articulated body pose estimation
 
Chapter 10: Part-based models
 
(II) Answering the public top questions about bag of words model.
 
(III) Real world examples for the usage of bag of words model in many fields.
 
Who this book is for
 
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of Bag of Words Model.
Available since: 05/13/2024.
Print length: 99 pages.

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