Visual Object Tracking with Deep Neural Networks

Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of...

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Формат: Online
Хэл сонгох:англи
Хэвлэсэн: IntechOpen 2021
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Онлайн хандалт:ONIX_20210420_9781789851588_2535
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collection Directory of Open Access Books
description Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research.
format Online
id doab-20.500.12854ir-67176
institution Directory of Open Access Books
language eng
publishDate 2021
publishDateRange 2021
publishDateSort 2021
publisher IntechOpen
publisherStr IntechOpen
record_format ojs
spelling doab-20.500.12854ir-671762024-04-14T10:28:21Z Visual Object Tracking with Deep Neural Networks Luigi Mazzeo, Pier Ramakrishnan, Srinivasan Spagnolo, Paolo Neural networks & fuzzy systems thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence Visual object tracking (VOT) and face recognition (FR) are essential tasks in computer vision with various real-world applications including human-computer interaction, autonomous vehicles, robotics, motion-based recognition, video indexing, surveillance and security. This book presents the state-of-the-art and new algorithms, methods, and systems of these research fields by using deep learning. It is organized into nine chapters across three sections. Section I discusses object detection and tracking ideas and algorithms; Section II examines applications based on re-identification challenges; and Section III presents applications based on FR research. 2021-04-20T16:05:27Z 2021-04-20T16:05:27Z 2019 book ONIX_20210420_9781789851588_2535 9781789851588 9781789851571 9781789851427 https://directory.doabooks.org/handle/20.500.12854/67176 eng image/jpeg n/a https://www.intechopen.com/books https://mts.intechopen.com/storage/books/8725/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/intechopen.80142 10.5772/intechopen.80142 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9781789851588 9781789851571 9781789851427 IntechOpen 206 open access
spellingShingle Neural networks & fuzzy systems
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
Visual Object Tracking with Deep Neural Networks
title Visual Object Tracking with Deep Neural Networks
title_full Visual Object Tracking with Deep Neural Networks
title_fullStr Visual Object Tracking with Deep Neural Networks
title_full_unstemmed Visual Object Tracking with Deep Neural Networks
title_short Visual Object Tracking with Deep Neural Networks
title_sort visual object tracking with deep neural networks
topic Neural networks & fuzzy systems
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
topic_facet Neural networks & fuzzy systems
thema EDItEUR::U Computing and Information Technology::UY Computer science::UYQ Artificial intelligence
url ONIX_20210420_9781789851588_2535