Domain Adaptation in Computer Vision with Deep Learning

Domain Adaptation in Computer Vision with Deep Learning
Author :
Publisher : Springer Nature
Total Pages : 258
Release :
ISBN-10 : 9783030455293
ISBN-13 : 3030455297
Rating : 4/5 (297 Downloads)

Book Synopsis Domain Adaptation in Computer Vision with Deep Learning by : Hemanth Venkateswara

Download or read book Domain Adaptation in Computer Vision with Deep Learning written by Hemanth Venkateswara and published by Springer Nature. This book was released on 2020-08-18 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art research in deep learning based domain adaptation. This book also discusses the various approaches to deep learning based domain adaptation in recent years. It outlines the importance of domain adaptation for the advancement of computer vision, consolidates the research in the area and provides the reader with promising directions for future research in domain adaptation. Divided into four parts, the first part of this book begins with an introduction to domain adaptation, which outlines the problem statement, the role of domain adaptation and the motivation for research in this area. It includes a chapter outlining pre-deep learning era domain adaptation techniques. The second part of this book highlights feature alignment based approaches to domain adaptation. The third part of this book outlines image alignment procedures for domain adaptation. The final section of this book presents novel directions for research in domain adaptation. This book targets researchers working in artificial intelligence, machine learning, deep learning and computer vision. Industry professionals and entrepreneurs seeking to adopt deep learning into their applications will also be interested in this book.


Domain Adaptation in Computer Vision with Deep Learning Related Books

Domain Adaptation in Computer Vision with Deep Learning
Language: en
Pages: 258
Authors: Hemanth Venkateswara
Categories: Computers
Type: BOOK - Published: 2020-08-18 - Publisher: Springer Nature

GET EBOOK

This book provides a survey of deep learning approaches to domain adaptation in computer vision. It gives the reader an overview of the state-of-the-art researc
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning
Language: en
Pages: 212
Authors: Shadi Albarqouni
Categories: Computers
Type: BOOK - Published: 2020-09-26 - Publisher: Springer

GET EBOOK

This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI W
Advanced Methods and Deep Learning in Computer Vision
Language: en
Pages: 584
Authors: E. R. Davies
Categories: Technology & Engineering
Type: BOOK - Published: 2021-11-09 - Publisher: Academic Press

GET EBOOK

Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emer
Visual Domain Adaptation in the Deep Learning Era
Language: en
Pages: 182
Authors: Gabriela Csurka
Categories: Computers
Type: BOOK - Published: 2022-06-06 - Publisher: Springer Nature

GET EBOOK

Solving problems with deep neural networks typically relies on massive amounts of labeled training data to achieve high performance. While in many situations hu
Synthetic Data for Deep Learning
Language: en
Pages: 348
Authors: Sergey I. Nikolenko
Categories: Computers
Type: BOOK - Published: 2021-06-26 - Publisher: Springer Nature

GET EBOOK

This is the first book on synthetic data for deep learning, and its breadth of coverage may render this book as the default reference on synthetic data for year