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Sol-gel processing and physic-chemical characterization of La and Ce doped lead titanate ceramics

Autor: Guaaybess Y., Maanan M., Adhiri R., Moussetad M., El Mesbahi A., Sayouri S., Zarhouni L.

Publikováno v: MATEC Web of Conferences, Vol 5, p 04036 (2013)

PbTiO3 (PT) sol gel processed powders doped with lanthanum (PLT14) and cerium (PLCexT14, x = 1; 3; 6; 10) were characterized by XRD and Raman spectroscopy. The samples crystallize in a pure perovskite phase at temperatures smaller than those reported

Externí odkaz: https://doaj.org/article/494a7811d7d4495fb0ae06bd3af39184

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USING MACHINE LEARNING COUPLED WITH REMOTE SENSING FOR FOREST FIRE SUSCEPTIBILITY MAPPING. CASE STUDY TETOUAN PROVINCE, NORTHERN MOROCCO

Autor: Seddouki, M., Benayad, M., Aamir, Z., Tahiri, M., Maanan, M., Rhinane, H.

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. :333-342

Currently there is a public awareness to protect the environment especially forest ecosystems and the forest fire dilemma has become a topic of intense research around the world. In this setting, this study evaluates forest fire susceptibility (FFS)

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e0b85f19f2ab0d167031833072d5668
https://doi.org/10.5194/isprs-archives-xlviii-4-w6-2022-333-2023

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USING YOLOV5 TO DETECT PLASTIC GREENHOUSES IN MOROCCO

Autor: Simou, M. R., Loulad, S., Aamir, Z., Maanan, M., Rhinane, H.

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. :351-354

Globally, Increasing greenhouse production is causing producing environmental issues. Monitoring the number and determining the locations of greenhouses are essential for the modern agricultural land management. The aim of this study was to detect pl

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ca864e596ab252bfc3457744e33949f8
https://doi.org/10.5194/isprs-archives-xlviii-4-w6-2022-351-2023

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GEOMEMBRANE BASINS DETECTION BASED ON SATELLITE HIGH-RESOLUTION IMAGERY USING DEEP LEARNING ALGORITHMS

Autor: Benayad, M., Houran, N., Aamir, Z., Maanan, M., Rhinane, H.

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. :75-79

Agriculture is a very important economic sector in Morocco, which requires a set of tools to improve agricultural production. Among these tools, the use of geomembrane basins. The latter is of great importance in smart farming planning, management pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4526fd2d82607c5c47f0d17924cf3139
https://doi.org/10.5194/isprs-archives-xlviii-4-w6-2022-75-2023

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RURAL SETTLEMENTS SEGMENTATION BASED ON DEEP LEARNING U-NET USING REMOTE SENSING IMAGES

Autor: Aamir, Z., Seddouki, M., Himmy, O., Maanan, M., Tahiri, M., Rhinane, H.

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. :1-5

Accurate and efficient extraction of rural settlements from high-resolution remote sensing imagery is of paramount importance for rural government management. Unplanned rural settlements are quite common. Understanding the spatial characteristic of t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::88eccd00bd88db6afffe7442fc48e4d5
https://doi.org/10.5194/isprs-archives-xlviii-4-w6-2022-1-2023

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Akademický článek

INTEGRATION OF DEEP LEARNING MODELS FOR VEHICLE COUNTING: TOWARDS OPTIMIZED PLANNING OF URBAN CHARGING INFRASTRUCTURES.

Autor: Benayad, M., Rochd, A., Houran, N., Simou, M. R., Maanan, M., Rhinane, H.

Publikováno v: International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences; 2024, Vol. 48 Issue 4/W9, p77-82, 6p

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MONITORING FOREST DEGRADATION OVER FOUR DECADES USING REMOTE SENSING AND MACHINE LEARNING CLASSIFICATION ALGORITHMS IN BOUSKOURA, MOROCCO.

Autor: Simou, M. R., Houran, N., Benayad, M., Maanan, M., Loulad, S., Rhinane, H.

Publikováno v: International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences; 2024, Vol. 48 Issue 4/W9, p337-342, 6p

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