S. Ameur

发表

Using naive Bayes classifier for classification of convective rainfall intensities based on spectral characteristics retrieved from SEVIRI

Slimane Hameg, M. Lazri, S. Ameur, 2016, Journal of Earth System Science.

Instantaneous rainfall estimation using neural network from multispectral observations of SEVIRI radiometer and its application in estimation of daily and monthly rainfall

M. Lazri, S. Ameur, Yacine Mohia, 2014 .

Infrared and Microwave Image Fusion for Rainfall Detection over Northern Algeria

M. Lazri, S. Ameur, Fethi Ouallouche, 2014 .

Novel SVM-based technique to improve rainfall estimation over the Mediterranean region (north of Algeria) using the multispectral MSG SEVIRI imagery

Soltane Ameur, Mourad Lazri, M. Lazri, 2017 .

Improvement of rainfall estimation from MSG data using Random Forests classification and regression

Soltane Ameur, Mourad Lazri, M. Lazri, 2018, Atmospheric Research.

A multilayer perceptron and multiclass support vector machine based high accuracy technique for daily rainfall estimation from MSG SEVIRI data

S. Ameur, Mounir Sehad, 2020 .

Color image compression based on wavelet transform and support vector regression

Mourad Lahdir, S. Ameur, Nadia Zikiou, 2014, International Image Processing, Applications and Systems Conference.

The solar radiation evaluation by satellite images processing

A. Mefti, A. Adane, S. Ameur, 2010 .

Novel WkNN-based technique to improve instantaneous rainfall estimation over the north of Algeria using the multispectral MSG SEVIRI imagery

M. Lazri, S. Ameur, Noureddine Bensafi, 2019, Journal of Atmospheric and Solar-Terrestrial Physics.

Extreme Learning Machine versus Multilayer perceptron for rainfall estimation from MSG Data

M. Lazri, S. Ameur, Fethi Ouallouche, 2022, E3S Web of Conferences.

Combination of Spectral and Textural Features in the MSG Satellite Remote Sensing Images for Classifying Rainy Area into Different Classes

M. Lazri, S. Ameur, Yacine Mohia, 2017, Journal of the Indian Society of Remote Sensing.

Multifractal analysis for improved osteoporosis classification

S. Ameur, B. Haddad, M. El Hassouni, 2023, Biomedical Signal Processing and Control.

Application of Dempster-Shafer theory for optimization of precipitation classification and estimation results from remote sensing data using machine learning

M. Lazri, S. Ameur, Fethi Ouallouche, 2023, Remote Sensing Applications: Society and Environment.

Improving satellite rainfall estimation from MSG data in Northern Algeria by using a multi-classifier model based on machine learning

Karim Labadi, Soltane Ameur, Mourad Lazri, 2020 .

Rainfall detection over northern Algeria by combining MSG and TRMM data

S. Ameur, Fethi Ouallouche, 2016, Applied Water Science.

Rainfall estimation over a Mediterranean region using a method based on various spectral parameters of SEVIRI-MSG

Soltane Ameur, Jacques Testud, Zohra Ameur, 2013 .

Behavior analysis of convective and stratiform rain using Markovian approach over Mediterranean region from meteorological radar data

Slimane Hameg, M. Lazri, S. Ameur, 2012 .

Analysis of drought areas in northern Algeria using Markov chains

Mourad Lahdir, M. Lazri, S. Ameur, 2015, Journal of Earth System Science.

Combination of support vector machine, artificial neural network and random forest for improving the classification of convective and stratiform rain using spectral features of SEVIRI data

Soltane Ameur, Mourad Lazri, M. Lazri, 2018 .

A satellite rainfall retrieval technique over northern Algeria based on the probability of rainfall intensities classification from MSG-SEVIRI

M. Lazri, S. Ameur, 2016 .

A local-spectral fuzzy segmentation for MSG multispectral images

S. Ameur, A. Bitam, 2013 .

Cloud classification using the textural features of Meteosat images

S. Ameur, H. Sauvageot, Z. Ameur, 2004 .

Measurements of Aerosol Optical and Microphysical Properties in Tizi Ouzou

P. Goloub, T. Podvin, S. Ameur, 2017 .

Optimization of One versus All-SVM using AdaBoost algorithm for rainfall classification and estimation from multispectral MSG data

M. Lazri, S. Ameur, Fethi Ouallouche, 2022, Advances in Space Research.

Classification of Precipitation Intensities from Remote Sensing Data Based on Artificial Intelligence Using RF Multi-learning

M. Lazri, S. Ameur, Fethi Ouallouche, 2023, Journal of the Indian Society of Remote Sensing.

Development of a hybrid classification technique based on deep learning applied to MSG / SEVIRI multispectral data

Karim Labadi, Soltane Ameur, Salim Oukali, 2019, Journal of Atmospheric and Solar-Terrestrial Physics.

Convective rainfall estimation from MSG/SEVIRI data based on different development phase duration of convective systems (growth phase and decay phase)

Soltane Ameur, Mourad Lazri, Jean Michel Brucker, 2014 .

Multispectral image segmentation using Gabor filtering and local homogeneity analysis with application to MSG

Soltane Ameur, Abdelmadjid Bitam, S. Ameur, 2013, 3rd International Conference on Systems and Control.

Enhancing hyperspectral image compression using learning-based super-resolution technique

Soltane Ameur, Mourad Lahdir, Mohand Ouahioune, 2021, Earth Science Informatics.

Distribution of Tropospheric Water Vapor in Clear and Cloudy Conditions from Microwave Radiometric Profiling

Nicolas Jeannin, Henri Sauvageot, Soltane Ameur, 2009 .

THE EFFECTIVENESS OF THE RADON TRANSFORM AGAINST THE QUANTIZATION NOISE

Soltane Ameur, Zohra Ameur, Mourad Lahdir, 2015 .

Meteosat image sequence coding in the Radon field

Mourad Lahdir, S. Ameur, M. Cherifi, 2019, Optik.

Precipitation estimation by a multi-threshold method using cloud optical and microphysical properties from MSG / SEVIRI data

M. Lazri, S. Ameur, J. Brucker, 2020 .

Image Segmentation Method for Identifying Convective and Stratiform Rain using MSG SEVIRI Data

M. Lazri, S. Ameur, Fethi Ouallouche, 2014 .

Identification of raining clouds using a method based on optical and microphysical cloud properties from Meteosat second generation daytime and nighttime data

J. Testud, Slimane Hameg, M. Lazri, 2013, Applied Water Science.