Conditional Field for Image Classification

Benbraika, Souad (2018) Conditional Field for Image Classification. Doctoral thesis, Mohamed Khidher University Biskra.

[img]
Preview
Text
thesis.pdf

Download (178MB) | Preview

Abstract

We propose a novel multi label (ML) classification approach based on the Conditional Random fields (CRF) for the high resolution UAV images. The inderlying idea of the proposed model integrate 1) spatial information within the same class; jointly with 2) cross-correlation information between different class labels after . The experiments were done on two different UAV image datasets and the experimental results show that the new model outperforms conventional approaches.

Item Type: Thesis (Doctoral)
Uncontrolled Keywords: Conditional random fields (CRF), Markovian random fields(MRF), Image multilabeling classification, Spatial contextual information, UAV images.
Subjects: Q Science > QA Mathematics
Divisions: Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie > Département de Mathématiques
Depositing User: BFSE
Date Deposited: 06 Jan 2019 08:24
Last Modified: 06 Jan 2019 08:24
URI: http://thesis.univ-biskra.dz/id/eprint/3839

Actions (login required)

View Item View Item