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Composing Fisher Kernels from Deep Neural Models

Composing Fisher Kernels from Deep Neural Models

-A Practitioner's Approach-

Tayyaba Azim; Sarah Ahmed

 

53,49 EUR
Lieferzeit 12-13 Tage



53,49 EUR
Lieferzeit 12-13 Tage



Autorinformation
Inhaltsverzeichnis
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Übersicht


Verlag : Springer International Publishing
Buchreihe : SpringerBriefs in Computer Science
Sprache : Englisch
Erschienen : 05. 09. 2018
Seiten : 59
Einband : Kartoniert
Höhe : 235 mm
Breite : 155 mm
Gewicht : 178 g
ISBN : 9783319985237
Sprache : Englisch

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Autorinformation


Dr. Tayyaba Azim is an Assistant Professor at the Center for Information Technology, Institute of Management Sciences, Peshawar, Pakistan. Sarah Ahmed is a current research student enrolled in Masters of Computer Science program at Institute of Management Sciences Peshawar, Pakistan. She has received her  Bachelor’s Degree in Computer Science from Edwardes College, Peshawar,Pakistan. Her areas of interest include: Machine Learning, Computer Vision and Data-Science. Currently, her research work is centered around the feature compression and selection approaches for Fisher vectors derived from deep neural models. Her research paper: "Compression techniques for Deep Fisher Vectors" was awarded  the best paper in the area of applications at ICPRAM conference 2017. 

Inhaltsverzeichnis


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.

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Deine Buchhandlung


Buchhandlung LeseLust
Inh. Gernod Siering

Georgenstraße 2
99817 Eisenach

03691/733822
kontakt@leselust-eisenach.de

Montag-Freitag 9-17 Uhr
Sonnabend 10-14 Uhr



Deine Buchhandlung
Buchhandlung LeseLust
Inh. Gernod Siering

Georgenstraße 2
99817 Eisenach

03691/733822
kontakt@leselust-eisenach.de

Montag-Freitag 9-17 Uhr
Sonnabend 10-14 Uhr