Unsupervised Learning in Space and Time

Name: Unsupervised Learning in Space and Time
Brand: Springer Nature Switzerland AG
SKU: 9783030421274
Price: 57295 HUF
Availability: InStock

A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks

Szerző: Marius Leordeanu

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer Nature Switzerland AG

Elérhetőség: Beszállítói készleten

Küldés 10-13 napon belül

57 295 Ft

This book addresses one of the most important unsolved problems in artificial intelligence: the task...

Információk a könyvről

Szerző

Marius Leordeanu

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

2020

oldal

298

EAN

9783030421274

Enbook ID

25610191

Kiadó

Springer Nature Switzerland AG

Súly

632

Méretek

162 x 242 x 25

Teljes leírás

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.

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Unsupervised Learning in Space and Time

A Modern Approach for Computer Vision using Graph-based Techniques and Deep Neural Networks

Információk a könyvről

Teljes leírás

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Azok a vásárlók, akik ezt a könyvet megvásárolták, a következőket is megvásárolták