The Resource Composing Fisher Kernels from Deep Neural Models : A Practitioner's Approach, by Tayyaba Azim, Sarah Ahmed, (electronic resource)

Composing Fisher Kernels from Deep Neural Models : A Practitioner's Approach, by Tayyaba Azim, Sarah Ahmed, (electronic resource)

Label
Composing Fisher Kernels from Deep Neural Models : A Practitioner's Approach
Title
Composing Fisher Kernels from Deep Neural Models
Title remainder
A Practitioner's Approach
Statement of responsibility
by Tayyaba Azim, Sarah Ahmed
Creator
Contributor
Author
Provider
Subject
Language
eng
Summary
Member of
http://library.link/vocab/creatorName
Azim, Tayyaba
Image bit depth
0
LC call number
  • Q337.5
  • TK7882.P3
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorName
  • Ahmed, Sarah.
  • SpringerLink
Series statement
SpringerBriefs in Computer Science,
http://library.link/vocab/subjectName
  • Computer science
  • Data structures (Computer science)
  • Mathematical statistics
  • Information storage and retrieval
  • Artificial intelligence
  • Pattern perception
  • Computer Science
  • Pattern Recognition
  • Signal, Image and Speech Processing
  • Information Storage and Retrieval
  • Probability and Statistics in Computer Science
  • Data Storage Representation
  • Artificial Intelligence (incl. Robotics)
Label
Composing Fisher Kernels from Deep Neural Models : A Practitioner's Approach, by Tayyaba Azim, Sarah Ahmed, (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1. Kernel Based Learning: A Pragmatic Approach in the Face of New Challenges -- Chapter 2. Fundamentals of Fisher Kernels -- Chapter 3. Training Deep Models and Deriving Fisher Kernels: A Step Wise Approach -- Chapter 4. Large Scale Image Retrieval and Its Challenges -- Chapter 5. Open Source Knowledge Base for Machine Learning Practitioners
Dimensions
unknown
Extent
XIII, 59 p. 6 illus., 5 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319985244
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-98524-4
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-319-98524-4
Label
Composing Fisher Kernels from Deep Neural Models : A Practitioner's Approach, by Tayyaba Azim, Sarah Ahmed, (electronic resource)
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
Chapter 1. Kernel Based Learning: A Pragmatic Approach in the Face of New Challenges -- Chapter 2. Fundamentals of Fisher Kernels -- Chapter 3. Training Deep Models and Deriving Fisher Kernels: A Step Wise Approach -- Chapter 4. Large Scale Image Retrieval and Its Challenges -- Chapter 5. Open Source Knowledge Base for Machine Learning Practitioners
Dimensions
unknown
Extent
XIII, 59 p. 6 illus., 5 illus. in color.
File format
multiple file formats
Form of item
electronic
Isbn
9783319985244
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other control number
10.1007/978-3-319-98524-4
Other physical details
online resource.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(DE-He213)978-3-319-98524-4

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