Scalable Bag of Subpaths Kernel for Learning on Hierarchical Image Representations and Multi-Source Remote Sensing Data Classification

Scalable Bag of Subpaths Kernel for Learning on Hierarchical Image Representations and Multi-Source Remote Sensing Data Classification

The geographic object-based image analysis (GEOBIA) framework has gained increasing interest for the last decade. One of its key advantages is the hierarchical representation of an image, where object topological features can be extracted and modeled in the form of structured data. We thus propose t...

Full description

Bibliographic Details
Main Authors: Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Remote Sensing
Subjects:
structured kernel
random Fourier features
kernel approximation
GEOBIA
hierarchical representations
large-scale machine learning
Online Access:http://www.mdpi.com/2072-4292/9/3/196

Internet

http://www.mdpi.com/2072-4292/9/3/196

Similar Items