9783030306700 - domain adaptation for visual understanding (11 resultados)
Domain Adaptation for Visual Understanding
Singh, Richa (EDT); Vatsa, Mayank (EDT); Patel, Vishal M. (EDT); Ratha, Nalini (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 122,07
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Condición: As New. Unread book in perfect condition.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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EUR 115,83
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Domain Adaptation for Visual Understanding
Singh, Richa (EDT); Vatsa, Mayank (EDT); Patel, Vishal M. (EDT); Ratha, Nalini (EDT)
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
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EUR 131,22
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Condición: New.
Domain Adaptation for Visual Understanding
Singh, Richa (EDT); Vatsa, Mayank (EDT); Patel, Vishal M. (EDT); Ratha, Nalini (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 115,81
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Domain Adaptation for Visual Understanding
Singh, Richa (EDT); Vatsa, Mayank (EDT); Patel, Vishal M. (EDT); Ratha, Nalini (EDT)
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 128,26
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 155,34
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Hardcover. Condición: Brand New. 156 pages. 9.25x6.10x0.59 inches. In Stock.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 106,99
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text presents a diverse se…lection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition.Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presentsa technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods.This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 86,24
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Condición: new. Questo è un articolo print on demand.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 106,99
Envío por EUR 23,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text prese…nts a diverse selection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition.Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presents a technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods.This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding. 156 pp. Englisch.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 92,27
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents the latest research on domain adaptation for visual understandingProvides perspectives from an international selection of authorities in the fieldReviews a variety of applications and techniquesDr.…Richa Singh&nbs.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 106,99
Envío por EUR 60,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This unique volume reviews the latest advances in domain adaptation in the training of machine learning algorithms for visual understanding, offering valuable insights from an international selection of experts in the field. The text presents…a diverse selection of novel techniques, covering applications of object recognition, face recognition, and action and event recognition.Topics and features: reviews the domain adaptation-based machine learning algorithms available for visual understanding, and provides a deep metric learning approach; introduces a novel unsupervised method for image-to-image translation, and a video segment retrieval model that utilizes ensemble learning; proposes a unique way to determine which dataset is most useful in the base training, in order to improve the transferability of deep neural networks; describes a quantitative method for estimating the discrepancy between the source and target data to enhance image classification performance; presentsa technique for multi-modal fusion that enhances facial action recognition, and a framework for intuition learning in domain adaptation; examines an original interpolation-based approach to address the issue of tracking model degradation in correlation filter-based methods.This authoritative work will serve as an invaluable reference for researchers and practitioners interested in machine learning-based visual recognition and understanding.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 156 pp. Englisch.
