Artículos relacionados a Unsupervised Learning in Space and Time: A Modern Approach...

Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks (Advances in Computer Vision and Pattern Recognition) - Tapa dura

 
9783030421274: Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks (Advances in Computer Vision and Pattern Recognition)

Sinopsis

This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field.

Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts.

Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way.

Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. 


"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Dr. Marius Leordeanu is an Associate Professor (Senior Lecturer) at the Computer Science & Engineering Department, Polytechnic University of Bucharest and a Senior Researcher at the Institute of Mathematics of the Romanian Academy (IMAR), Bucharest, Romania. In 2014, he was awarded the Grigore Moisil Prize, the most prestigious award in mathematics bestowed by the Romanian Academy, for his work on unsupervised learning.


De la contraportada

This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field.

Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts.

Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way.

Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines.

Dr. Marius Leordeanu is an Associate Professor (Senior Lecturer) at the Computer Science & Engineering Department, Polytechnic University of Bucharest and a Senior Researcher at the Institute of Mathematics of the Romanian Academy (IMAR), Bucharest, Romania. In 2014, he was awarded the Grigore Moisil Prize, the most prestigious award in mathematics bestowed by the Romanian Academy, for his work on unsupervised learning.

"Sobre este título" puede pertenecer a otra edición de este libro.

  • EditorialSpringer
  • Año de publicación2020
  • ISBN 10 3030421279
  • ISBN 13 9783030421274
  • EncuadernaciónTapa dura
  • IdiomaInglés
  • Número de edición1
  • Número de páginas324
  • Contacto del fabricanteno disponible

Comprar usado

Condición: Como Nuevo
Unread book in perfect condition...
Ver este artículo

EUR 17,45 gastos de envío desde Estados Unidos de America a España

Destinos, gastos y plazos de envío

Comprar nuevo

Ver este artículo

EUR 9,47 gastos de envío desde Reino Unido a España

Destinos, gastos y plazos de envío

Otras ediciones populares con el mismo título

9783030421304: Unsupervised Learning in Space and Time: A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks (Advances in Computer Vision and Pattern Recognition)

Edición Destacada

ISBN 10:  3030421309 ISBN 13:  9783030421304
Editorial: Springer, 2021
Tapa blanda

Resultados de la búsqueda para Unsupervised Learning in Space and Time: A Modern Approach...

Imagen de archivo

LEORDEANU, MARIUS
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: Speedyhen, London, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: NEW. Nº de ref. del artículo: NW9783030421274

Contactar al vendedor

Comprar nuevo

EUR 119,77
Convertir moneda
Gastos de envío: EUR 9,47
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen de archivo

Marius Leordeanu
Publicado por Springer Nature Switzerland AG, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: PBShop.store UK, Fairford, GLOS, Reino Unido

Calificación del vendedor: 4 de 5 estrellas Valoración 4 estrellas, Más información sobre las valoraciones de los vendedores

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: GB-9783030421274

Contactar al vendedor

Comprar nuevo

EUR 135,23
Convertir moneda
Gastos de envío: EUR 4,39
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen de archivo

Marius Leordeanu
Publicado por Springer Nature Switzerland AG, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: GB-9783030421274

Contactar al vendedor

Comprar nuevo

EUR 140,54
Convertir moneda
Gastos de envío: EUR 1,07
De Estados Unidos de America a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen del vendedor

Leordeanu, Marius
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: GreatBookPricesUK, Woodford Green, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. Nº de ref. del artículo: 41299663-n

Contactar al vendedor

Comprar nuevo

EUR 135,22
Convertir moneda
Gastos de envío: EUR 17,78
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen del vendedor

Leordeanu, Marius
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. Nº de ref. del artículo: 41299663-n

Contactar al vendedor

Comprar nuevo

EUR 138,15
Convertir moneda
Gastos de envío: EUR 17,45
De Estados Unidos de America a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen de archivo

Marius Leordeanu
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: Chiron Media, Wallingford, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. Nº de ref. del artículo: 6666-GRD-9783030421274

Contactar al vendedor

Comprar nuevo

EUR 139,62
Convertir moneda
Gastos de envío: EUR 17,77
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Imagen de archivo

Leordeanu
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: Ria Christie Collections, Uxbridge, Reino Unido

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: New. In. Nº de ref. del artículo: ria9783030421274_new

Contactar al vendedor

Comprar nuevo

EUR 153,50
Convertir moneda
Gastos de envío: EUR 4,72
De Reino Unido a España
Destinos, gastos y plazos de envío

Cantidad disponible: Más de 20 disponibles

Añadir al carrito

Imagen del vendedor

Marius Leordeanu
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura
Impresión bajo demanda

Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field.Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts.Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way.Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. 324 pp. Englisch. Nº de ref. del artículo: 9783030421274

Contactar al vendedor

Comprar nuevo

EUR 160,49
Convertir moneda
Gastos de envío: EUR 11,00
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 2 disponibles

Añadir al carrito

Imagen del vendedor

Marius Leordeanu
Publicado por Springer International Publishing, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Nuevo Tapa dura

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book addresses one of the most important unsolved problems in artificial intelligence: the task of learning, in an unsupervised manner, from massive quantities of spatiotemporal visual data that are available at low cost. The book covers important scientific discoveries and findings, with a focus on the latest advances in the field.Presenting a coherent structure, the book logically connects novel mathematical formulations and efficient computational solutions for a range of unsupervised learning tasks, including visual feature matching, learning and classification, object discovery, and semantic segmentation in video. The final part of the book proposes a general strategy for visual learning over several generations of student-teacher neural networks, along with a unique view on the future of unsupervised learning in real-world contexts.Offering a fresh approach to this difficult problem, several efficient, state-of-the-art unsupervised learning algorithms are reviewed in detail, complete with an analysis of their performance on various tasks, datasets, and experimental setups. By highlighting the interconnections between these methods, many seemingly diverse problems are elegantly brought together in a unified way.Serving as an invaluable guide to the computational tools and algorithms required to tackle the exciting challenges in the field, this book is a must-read for graduate students seeking a greater understanding of unsupervised learning, as well as researchers in computer vision, machine learning, robotics, and related disciplines. Nº de ref. del artículo: 9783030421274

Contactar al vendedor

Comprar nuevo

EUR 160,49
Convertir moneda
Gastos de envío: EUR 11,99
De Alemania a España
Destinos, gastos y plazos de envío

Cantidad disponible: 2 disponibles

Añadir al carrito

Imagen del vendedor

Leordeanu, Marius
Publicado por Springer, 2020
ISBN 10: 3030421279 ISBN 13: 9783030421274
Antiguo o usado Tapa dura

Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America

Calificación del vendedor: 5 de 5 estrellas Valoración 5 estrellas, Más información sobre las valoraciones de los vendedores

Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 41299663

Contactar al vendedor

Comprar usado

EUR 155,32
Convertir moneda
Gastos de envío: EUR 17,45
De Estados Unidos de America a España
Destinos, gastos y plazos de envío

Cantidad disponible: 1 disponibles

Añadir al carrito

Existen otras 7 copia(s) de este libro

Ver todos los resultados de su búsqueda