High-Order Models in Semantic Image Segmentation (notice n° 1331285)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02083cam a2200277zu 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | FRCYB88965955 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250429184238.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250429s2023 fr | o|||||0|0|||eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9780128053201 |
| 035 ## - SYSTEM CONTROL NUMBER | |
| System control number | FRCYB88965955 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | FR-PaCSA |
| Language of cataloging | en |
| Transcribing agency | |
| Description conventions | rda |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Ben Ayed, Ismail |
| 245 01 - TITLE STATEMENT | |
| Title | High-Order Models in Semantic Image Segmentation |
| Statement of responsibility, etc. | ['Ben Ayed, Ismail'] |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Name of producer, publisher, distributor, manufacturer | Academic Press |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | p. |
| 336 ## - CONTENT TYPE | |
| Content type code | txt |
| Source | rdacontent |
| 337 ## - MEDIA TYPE | |
| Media type code | c |
| Source | rdamdedia |
| 338 ## - CARRIER TYPE | |
| Carrier type code | c |
| Source | rdacarrier |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | High-Order Models in Semantic Image Segmentation reviews recent developments in optimization-based methods for image segmentation, presenting several geometric and mathematical models that underlie a broad class of recent segmentation techniques. Focusing on impactful algorithms in the computer vision community in the last 10 years, the book includes sections on graph-theoretic and continuous relaxation techniques, which can compute globally optimal solutions for many problems. The book provides a practical and accessible introduction to these state-of -the-art segmentation techniques that is ideal for academics, industry researchers, and graduate students in computer vision, machine learning and medical imaging. - Gives an intuitive and conceptual understanding of this mathematically involved subject by using a large number of graphical illustrations - Provides the right amount of knowledge to apply sophisticated techniques for a wide range of new applications - Contains numerous tables that compare different algorithms, facilitating the appropriate choice of algorithm for the intended application - Presents an array of practical applications in computer vision and medical imaging - Includes code for many of the algorithms that is available on the book's companion website |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Ben Ayed, Ismail |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Access method | Cyberlibris |
| Uniform Resource Identifier | <a href="https://international.scholarvox.com/netsen/book/88965955">https://international.scholarvox.com/netsen/book/88965955</a> |
| Electronic format type | text/html |
| Host name | |
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