Visual Object Tracking Deep (67 results)

- Softcover
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- Softcover
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- Softcover
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- Softcover
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Paperback. Condition: New. This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also:Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methodsElaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexityIllustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenariosExplores the future research directions for visual tracking by analyzing the real-time applicationsThe book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.…

- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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- Softcover
- International Edition
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Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

- Softcover
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Taschenbuch. Condition: Neu. Visual Object Tracking using Deep Learning | Ashish Kumar | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | CRC Press | EAN 9781032598079 | Verantwortliche Person für die EU: Taylor & Francis Verlag GmbH, Kaufingerstr. 24, 80331 München, gpsr[at]taylorandfrancis[dot]com | Anbieter: preigu. …

- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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Visual Object Tracking from Correlation Filter to Deep Learning
Weiwei Xing, Weibin Liu, Jun Wang, Bowen Song, Lihui Wang, Yuxiang Yang, Shunli Zhang
- Hardcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.…

Visual Object Tracking From Correlation Filter to Deep Learning [Hardcover] [Nov 19, 2021] Xing, Weiwei; Liu, Weibin; Wang, Jun; Zhang, Shunli; Wang, Lihui; Yang, Yuxiang and Song, Bowen
Xing, Weiwei; Liu, Weibin; Wang, Jun; Zhang, Shunli; Wang, Lihui; Yang, Yuxiang; Song, Bowen
- Hardcover
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- Hardcover
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Visual Object Tracking from Correlation Filter to Deep Learning
Xing, Weiwei; Liu, Weibin; Wang, Jun; Zhang, Shunli; Wang, Lihui; Yang, Yuxiang; Song, Bowen
- Softcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Hardcover
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- Softcover
Seller: Rarewaves.com UK, London, United KingdomRarewaves.com UK
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Paperback. Condition: New. This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed. The book also:Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methodsElaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexityIllustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenariosExplores the future research directions for visual tracking by analyzing the real-time applicationsThe book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.…

Visual Object Tracking from Correlation Filter to Deep Learning
Weiwei Xing, Weibin Liu, Jun Wang, Bowen Song, Lihui Wang, Yuxiang Yang, Shunli Zhang
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
Contact seller5-star sellerCondition: Used
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US$ 120.60 shippingShips from Germany to U.S.A.Quantity: 2 available
Condition: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | The book focuses on visual object tracking systems and approaches based on correlation filter and deep learning. Both foundations and implementations have been addressed. The algorithm, system design and performance evaluation have been explored for three kinds of tracking methods including correlation filter based methods, correlation filter with deep feature based methods, and deep learning based methods. Firstly, context aware and multi-scale strategy are presented in correlation filter based trackers; then, long-short term correlation filter, context aware correlation filter and auxiliary relocation in SiamFC framework are proposed for combining correlation filter and deep learning in visual object tracking; finally, improvements in deep learning based trackers including Siamese network, GAN and reinforcement learning are designed. The goal of this book is to bring, in a timely fashion, the latest advances and developments in visual object tracking, especially correlation filter and deep learning based methods, which is particularly suited for readers who are interested in the research and technology innovation in visual object tracking and related fields.…

- Hardcover
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- Softcover
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