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CIVR
2006
Springer

A Multi-feature Optimization Approach to Object-Based Image Classification

14 years 4 months ago
A Multi-feature Optimization Approach to Object-Based Image Classification
This paper proposes a novel approach for the construction and use of multi-feature spaces in image classification. The proposed technique combines low-level descriptors and defines suitable metrics. It aims at representing and measuring similarity between semantically meaningful objects within the defined multi-feature space. The approach finds the best linear combination of predefined visual descriptor metrics using a Multi-Objective Optimization technique. The obtained metric is then used to fuse multiple non-linear descriptors is be achieved and applied in image classification.
Qianni Zhang, Ebroul Izquierdo
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where CIVR
Authors Qianni Zhang, Ebroul Izquierdo
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