Taschenbuch. Condici�n: 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 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; 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. N� de ref. del art�culo: 9783030306731

Contactar al vendedor

Comprar nuevo

EUR 106,99

Convertir moneda

Gastos de env�o: EUR 23,00

De Alemania a Estados Unidos de America

Destinos, gastos y plazos de env�o

Cantidad disponible: 2 disponibles

A�adir al carrito

Imagen de archivo

Domain Adaptation for Visual Understanding

Publicado por Springer, 2021

ISBN 10: 3030306739 ISBN 13: 9783030306731

Nuevo Tapa blanda

Librería: Ria Christie Collections, Uxbridge, Reino Unido

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. In. N� de ref. del art�culo: ria9783030306731_new

Contactar al vendedor

Comprar nuevo

EUR 118,00

Convertir moneda

Gastos de env�o: EUR 14,25

De Reino Unido a Estados Unidos de America

Destinos, gastos y plazos de env�o

Cantidad disponible: M�s de 20 disponibles

A�adir al carrito

Imagen de archivo

Domain Adaptation for Visual Understanding

Publicado por Springer, 2021

ISBN 10: 3030306739 ISBN 13: 9783030306731

Nuevo Tapa blanda

Librería: California Books, Miami, FL, Estados Unidos de America

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. N� de ref. del art�culo: I-9783030306731

Contactar al vendedor

Comprar nuevo

EUR 132,86

Convertir moneda

Gastos de env�o: GRATIS

A Estados Unidos de America

Destinos, gastos y plazos de env�o

Cantidad disponible: M�s de 20 disponibles

A�adir al carrito

Imagen del vendedor

Domain Adaptation for Visual Understanding

Richa Singh

Publicado por Springer International Publishing, 2021

ISBN 10: 3030306739 ISBN 13: 9783030306731

Nuevo Taschenbuch

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: 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 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. N� de ref. del art�culo: 9783030306731

Contactar al vendedor

Comprar nuevo

EUR 106,99

Convertir moneda

Gastos de env�o: EUR 29,23

De Alemania a Estados Unidos de America

Destinos, gastos y plazos de env�o

Cantidad disponible: 1 disponibles

A�adir al carrito

Imagen del vendedor

Domain Adaptation for Visual Understanding

Singh, Richa|Vatsa, Mayank|Patel, Vishal M.|Ratha, Nalini

Publicado por Springer International Publishing, 2021

ISBN 10: 3030306739 ISBN 13: 9783030306731

Nuevo Tapa blanda

Impresi�n bajo demanda

Librería: moluna, Greven, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: 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. N� de ref. del art�culo: 458540602

Contactar al vendedor