Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Radja Kheddam"'
Publikováno v:
Journal of Applied Remote Sensing. 17
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0810f869ea77b7f4f6aa75665734766e
https://doi.org/10.1117/1.jrs.17.014511
https://doi.org/10.1117/1.jrs.17.014511
Publikováno v:
2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30b728398a4e3c08d567872a2207c945
https://doi.org/10.1109/icateee57445.2022.10093749
https://doi.org/10.1109/icateee57445.2022.10093749
Publikováno v:
ISIVC
In this paper, we shall describe a statistical approach for land change detection and extraction based on multivariate alteration detection (MAD) transformation combined with three thresholding methods. Unlike the most other multivariate change detec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7ef0b62dd64bdfef9fab158fbf6b258f
https://doi.org/10.1109/isivc.2018.8709197
https://doi.org/10.1109/isivc.2018.8709197
Publikováno v:
ATSIP
In this paper we shall describe a statistical approach for land change detection based on multivariate alteration detection (MAD) transformation combined with a thresholding method based on Chi squared test. Unlike the most other multivariate change
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c65289c656f6d2960ed27e1c73300c42
https://doi.org/10.1109/atsip.2018.8364501
https://doi.org/10.1109/atsip.2018.8364501
Publikováno v:
2017 5th International Conference on Electrical Engineering - Boumerdes (ICEE-B).
This paper deals with an unsupervised approach for land change detection and extraction using bitemporal and multispectral remotely sensed images. It is a statistical approach based on multivariate alteration detection (MAD) transformation combined w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::36f778da27d873c27c5c1d301e25bdb0
https://doi.org/10.1109/icee-b.2017.8192208
https://doi.org/10.1109/icee-b.2017.8192208
Publikováno v:
ATSIP
The aim of this paper is to present a new unsupervised classification method for satellite multispectral images based on affinity propagation (AP) algorithm. Recently proposed, affinity propagation becomes the most widely methods for data clustering.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::db7fb72c85e6e783ca8ae4321c625afe
https://doi.org/10.1109/atsip.2017.8075579
https://doi.org/10.1109/atsip.2017.8075579
Publikováno v:
ATSIP
In this paper, we present fusion and classification process of change indices using multitemporal satellites images in the aim to detect the change of surface states after a flood. This process is performed in the framework of Dempster Shafer Theory
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f93510711b051d42e24ee50d5b18ae2
https://doi.org/10.1109/atsip.2017.8075574
https://doi.org/10.1109/atsip.2017.8075574
Publikováno v:
Journal of Applied Remote Sensing. 12:1
Bayesian network classifiers (BNCs) are now among the most used supervised probabilistic methods for remote sensing image classification. Our contribution lies in two principal points. First, the investigation of the applicability of Kruskal’s algo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f0802e038608cd3349758d1f504af573
https://doi.org/10.1117/1.jrs.12.036007
https://doi.org/10.1117/1.jrs.12.036007
Publikováno v:
2015 First International Conference on New Technologies of Information and Communication (NTIC).
Support Vector Machines (SVM) and Maximum Likelihood (MLLH) are the most popular remote sensing image classification approaches. In the past, SVM and MLLH have been tested and evaluated only as pixel-based image classifiers. Moving from pixel-based a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::034c63b3fc2d46390acfb9ca6baf86fa
https://doi.org/10.1109/ntic.2015.7368750
https://doi.org/10.1109/ntic.2015.7368750
Publikováno v:
IPTA
The development of robust object-oriented classification approaches suitable for medium to high spatial resolution satellite imagery provides a valid alternative to traditional pixel-based classification approaches. In the past, Support Vector Machin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bc9f2163f2098b5ab6fc48c32209213a
https://doi.org/10.1109/ipta.2015.7367091
https://doi.org/10.1109/ipta.2015.7367091