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5 produkter
Covariances in Computer Vision and Machine Learning
Av Hà Quang Minh, Vittorio Murino
Häftad, 2017
625 kr
Lägg i varukorg
Covariance matrices play important roles in many areas of mathematics, statistics, and machine learning, as well as their applications. In computer vision and image processing, they give rise to a powerful data representation, namely the covariance descriptor, with numerous practical …
Covariances in Computer Vision and Machine Learning
Av Vittorio Murino, Ha Quang Minh
E-bok, 2022
821 kr
Lägg i varukorg
Covariance matrices play important roles in many areas of mathematics, statistics, and machine learning, as well as their applications. In computer vision and image processing, they give rise to a powerful data representation, namely the covariance descriptor, with numerous practical applications. …
Algorithmic Advances in Riemannian Geometry and Applications
For Machine Learning, Computer Vision, Statistics, and Optimization
Av Hà Quang Minh, Vittorio Murino
Inbunden, 2016
1580 kr
Lägg i varukorg
This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using …
Algorithmic Advances in Riemannian Geometry and Applications
For Machine Learning, Computer Vision, Statistics, and Optimization
Av Vittorio Murino, Ha Quang Minh
E-bok, 2016
1948 kr
Lägg i varukorg
This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using …
Algorithmic Advances in Riemannian Geometry and Applications
For Machine Learning, Computer Vision, Statistics, and Optimization
Av Hà Quang Minh, Vittorio Murino
Häftad, 2018
1534 kr
Lägg i varukorg
This book presents a selection of the most recent algorithmic advances in Riemannian geometry in the context of machine learning, statistics, optimization, computer vision, and related fields. The unifying theme of the different chapters in the book is the exploitation of the geometry of data using …