What Is Image Retrieval
A computer system that is used for browsing, searching, and retrieving images from a vast collection of digital images is called an image retrieval system (sometimes abbreviated as IRMS). In order for image retrieval to be carried out over the annotation words, the majority of the conventional and widespread methods currently in use include the addition of information to the images themselves. This metadata can take the form of captioning, keywords, titles, or descriptions. Annotating images manually is a significant investment of time, effort, and money; as a result, a significant amount of effort and research has been put into developing automatic image annotation methods. In addition, the proliferation of social web apps as well as the semantic web has been a driving force behind the development of a number of picture annotation tools that are web-based.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Image retrieval
Chapter 2: Information retrieval
Chapter 3: MPEG-7
Chapter 4: Content-based image retrieval
Chapter 5: Automatic image annotation
Chapter 6: Image organizer
Chapter 7: Google Images
Chapter 8: Image meta search
Chapter 9: Metadata
Chapter 10: Reverse image search
(II) Answering the public top questions about image retrieval.
(III) Real world examples for the usage of image retrieval in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of image retrieval' technologies.
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 image retrieval.
What Is Image Retrieval
A computer system that is used for browsing, searching, and retrieving images from a vast collection of digital images is called an image retrieval system (sometimes abbreviated as IRMS). In order for image retrieval to be carried out over the annotation words, the majority of the conventional and widespread methods currently in use include the addition of information to the images themselves. This metadata can take the form of captioning, keywords, titles, or descriptions. Annotating images manually is a significant investment of time, effort, and money; as a result, a significant amount of effort and research has been put into developing automatic image annotation methods. In addition, the proliferation of social web apps as well as the semantic web has been a driving force behind the development of a number of picture annotation tools that are web-based.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Image retrieval
Chapter 2: Information retrieval
Chapter 3: MPEG-7
Chapter 4: Content-based image retrieval
Chapter 5: Automatic image annotation
Chapter 6: Image organizer
Chapter 7: Google Images
Chapter 8: Image meta search
Chapter 9: Metadata
Chapter 10: Reverse image search
(II) Answering the public top questions about image retrieval.
(III) Real world examples for the usage of image retrieval in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of image retrieval' technologies.
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 image retrieval.
Image Retrieval: Fundamentals and Applications
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Image Retrieval: Fundamentals and Applications
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Product Details
| BN ID: | 2940167606425 |
|---|---|
| Publisher: | One Billion Knowledgeable |
| Publication date: | 07/06/2023 |
| Series: | Artificial Intelligence , #243 |
| Sold by: | PUBLISHDRIVE KFT |
| Format: | eBook |
| Pages: | 73 |
| File size: | 263 KB |