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An Introduction to Deep Convolutional Neural Nets for Computer Vision

Srinivas, Suraj and Sarvadevabhatla, Ravi K and Mopuri, Konda R and Prabhu, Nikita and Kruthiventi, Srinivas SS and Babu, R Venkatesh (2017) An Introduction to Deep Convolutional Neural Nets for Computer Vision. [Book Chapter]

Full text not available from this repository.
Official URL: https://doi.org/10.1016/B978-0-12-810408-8.00003-1


Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep learning techniques have offered a compelling alternative - that of automatically learning problem-specific features. With this new paradigm, every problem in computer vision is now being re-examined from a deep learning perspective. Therefore, it has become important to understand what kind of deep networks are suitable for a given problem. We specifically consider one form of deep networks widely used in computer vision - convolutional neural networks (CNNs). We start with "AlexNet" as our base CNN and then examine the broad variations proposed over time for many applications. We hope that our recipe-style presentation will serve as a guide, particularly for novice practitioners intending to use deep-learning techniques for computer vision.

Item Type: Book Chapter
Publisher: Elsevier Inc.
Additional Information: The copyright for this article belongs to the Elsevier Inc.
Keywords: Computer vision; Convolutional neural network; Deep learning; Image classification; Recurrent neural networks
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Division of Interdisciplinary Sciences > Supercomputer Education & Research Centre
Date Deposited: 29 May 2022 08:45
Last Modified: 31 May 2022 00:47
URI: https://eprints.iisc.ac.in/id/eprint/72801

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