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Erschienen in:
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2020 | OriginalPaper | Buchkapitel

Deep Learning Architectures for Computer Vision Applications: A Study

verfasst von : Randheer Bagi, Tanima Dutta, Hari Prabhat Gupta

Erschienen in: Advances in Data and Information Sciences

Verlag: Springer Singapore

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Abstract

Deep learning has become one of the most preferred solution for many complex problems. It shows outstanding performance in the field of computer vision to perform tasks like, image classification, object detection, and image generation. Recently, many research efforts are focused on changing the deep learning architecture for widespread application domain. In this paper, we present a comprehensive survey on the various issues and challenges faced by deep learning techniques. Furthermore, we analyze different deep learning architectures to provide the solution for the computer vision tasks along with their importance.

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Vorheriges Kapitel Minimizing Synchronization Error in Compressed Domain Watermarking
Nächstes Kapitel Robust Reversible Watermarking for Grayscale Medical Images
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Metadaten
Titel
Deep Learning Architectures for Computer Vision Applications: A Study
verfasst von
Randheer Bagi
Tanima Dutta
Hari Prabhat Gupta
Copyright-Jahr
2020
Verlag
Springer Singapore
Buch
Advances in Data and Information Sciences

Print ISBN: 978-981-15-0693-2

Electronic ISBN: 978-981-15-0694-9

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-981-15-0694-9_56

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