Tayyaba Azim, Sarah Ahmed

eBook, PDF

Composing Fisher Kernels from Deep Neural Models (eBook, PDF)

A Practitioner's Approach

Beschreibung

Composing Fisher Kernels from Deep Neural Models (eBook, PDF)

Technische Details

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• Größe: 2.39MB

Barrierefreiheit

• Text-to-Speech

Autor

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.

Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 59
• Erscheinungstermin: 23. August 2018
• Englisch
• ISBN-13: 9783319985244
• Artikelnr.: 53679469