EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 726 (2026) E3S Web Conf., 726 (2026) 01056 References
Open Access
Issue
E3S Web Conf.
Volume 726, 2026
The Second International Congress on Environment, Energy, and Materials for Sustainable Development Technology (IC2EM-SDT’26)
Article Number 01056
Number of page(s) 16
DOI https://doi.org/10.1051/e3sconf/202672601056
Published online 13 July 2026
  1. T. Mikkonen, “Capacity monitoring using object detection algorithms,” 2021. [Online]. Available: https://www.theseus.fi/handle/10024/748446 [Google Scholar]
  2. F. Rotella and I. Zambettakis, “Commande des systèmes par platitude,” Tech. l’Ingénieur, 2007. [Online]. Available: https://www.techniques-ingenieur.fr/base-documentaire/automatique-robotique-th16/commande-et-regulation-42394210/commande-des-systemes-par-platitude-s7450/ [Google Scholar]
  3. M. Hamedian, “Automatic classification of cardiomegaly using deep convolutional neural network,” 2022. [Online]. Available: https://www.theseus.fi/handle/10024/783174 [Google Scholar]
  4. Y. LeCun, “L’apprentissage profond, une révolution en intelligence artificielle,” Lett. Collège Fr., no. 41, p. 13, 2016. [Google Scholar]
  5. T. H. Eddine, “La détection d’objet avec OpenCV et deep learning,” 2020. [Online]. Available: http://archives.univ-biskra.dz/bitstream/123456789/17856/1/Trad_Houssem_Eddine.pdf [Google Scholar]
  6. T. Cheng, X. Wang, L. Huang, and W. Liu, “Boundary-Preserving Mask R-CNN, " in Computer Vision-ECCV 2020, vol. 12359, A. Vedaldi et al., Eds. Cham: Springer International Publishing, 2020, pp. 660–676. doi: 10.1007/978-3-030-58568-6_39. [Google Scholar]
  7. A. Panesar, Machine learning and AI for healthcare. Coventry, UK: Apress, 2019, pp. 1–73. [Google Scholar]
  8. M. J. Richard, F. Dufour, and S. Tarasiewicz, “Commande des robots manipulateurs par la programmation dynamique,” Mech. Mach. Theory, vol. 28, no. 3, pp. 301–316, 1993. [Google Scholar]
  9. F. Morbidi, “Cooperative Multi-robot Systems: From Perception to Action,” PhD thesis, Université de Picardie Jules Verne, 2024. [Online]. Available: https://hal.science/tel-04538462/ [Google Scholar]
  10. A. Khan, A. Sohail, U. Zahoora, and A. S. Qureshi, “A survey of the recent architectures of deep convolutional neural networks,” Artif. Intell. Rev., vol. 53, no. 8, pp. 5455–5516, Dec. 2020, doi: 10.1007/s10462-020-09825-6. [CrossRef] [Google Scholar]
  11. I. Bahri, M. Laib, and M. El, “Combinaison SVM et apprentissage profond pour la reconnaissance de caracteres arabe,” PhD thesis, Univ. Ahmed Draia of Adrar, 2022. [Google Scholar]
  12. Q. Akwiwu, “Object detection, segmentation, and distance estimation using YOLOv8,” 2025. [Online]. Available: https://www.theseus.fi/bitstream/handle/10024/888646/OBJECT%20DETECTION_SEGMENTATION_AND%20DISTANCE%20ESTIMATION%20WITH%20YOLOV8.pdf [Google Scholar]
  13. R. Naddaf, “Voix plurielles,” 2024. [Online]. Available: https://recherche.aphp.fi7wp-content/blogs.dir/77/files/2024/10/D2024_2024Newsletter_v5.pdf [Google Scholar]
  14. A. Jurkat, R. Klump, and F. Schneider, “Tracking the Rise of Robots: The IFR Database,” Jahrb. für Natl. und Stat., vol. 242, no. 5-6, pp. 669–689, Dec. 2022, doi: 10.1515/jbnst-2021-0059. [Google Scholar]
  15. J. J. Craig, Introduction to robotics: mechanics and control, 3rd ed. India: Pearson Education, 2009. [Google Scholar]
  16. I. Passas, “Bibliometric analysis: the main steps,” Encyclopedia, vol. 4, no. 2, 2024. [Online]. Available: https://www.mdpi.com/2673-8392/4/2/65 [Google Scholar]
  17. M. Aria and C. Cuccurullo, “bibliometrix : un outil R pour une analyse complète de la cartographie scientifique,” J. Informetr., vol. 11, no. 4, pp. 959–975, Nov. 2017, doi: 10.1016/j.joi.2017.08.007. [CrossRef] [Google Scholar]
  18. A. F. Choudhri, A. Siddiqui, N. R. Khan, and H. L. Cohen, “Understanding Bibliometric Parameters and Analysis,” RadioGraphics, vol. 35, no. 3, pp. 736–746, May 2015, doi: 10.1148/rg.2015140036. [Google Scholar]
  19. H. M. Alaoui, “Traces computationnelles du savoir et transformation numérique: nouvelles perspectives pour la gestion des connaissances à l’ère de l’intelligence artificielle,” Afr. Sci. J., vol. 3, no. 33, p. 911, 2025. [Google Scholar]
  20. V. Larivière, “Bibliométrie,” 2015. [Online]. Available: http://hdl.handle.net/1866/23203 [Google Scholar]
  21. M. A. Koseoglu, R. Rahimi, F. Okumus, and J. Liu, “Bibliometric studies in tourism, "Ann. Tour. Res., vol. 61, pp. 180–198, 2016. [Google Scholar]
  22. O. Öztürk, R. Kocaman, and D. K. Kanbach, “How to design bibliometric research: an overview and a framework proposal,” Rev. Manag. Sci., vol. 18, no. 11, pp. 3333–3361, Nov. 2024, doi: 10.1007/s11846-024-00738-0. [Google Scholar]
  23. H. Ouakhir et al., “Assessment of suspended sediment transport and associated sediment patterns in the Mkhdach catchment (Middle Atlas Mountainous/Morocco),” Model. Earth Syst. Environ., vol. 11, no. 4, p. 291, Jun. 2025, doi: 10.1007/s40808-025-02475-z. [Google Scholar]
  24. H. Save, S. Bettadpur, and B. D. Tapley, “High-resolution CSR GRACE RL05 mascons, " JGR Solid Earth, vol. 121, no. 10, pp. 7547- 7569, Oct. 2016, doi: 10.1002/2016JB013007. [Google Scholar]
  25. I. Zupic and T. Cater, “Bibliometric Methods in Management and Organization, " Organ. Res. Methods, vol. 18, no. 3, pp. 429T72, Jul. 2015, doi: 10.1177/1094428114562629. [CrossRef] [Google Scholar]
  26. M. Rodell et al., “The global land data assimilation system, " Bull. Am. Meteorol. Soc., vol. 85, no. 3, pp. 381–394, 2004. [Google Scholar]
  27. Y. Le Conte and M. Navajas, “Climate change: impact on honey bee populations and diseases, " Rev. Sci. Tech. Off. Int. Epizoot., vol. 27, no. 2, pp. 499–510, 2008. [Google Scholar]
  28. I. Kalu, C. E. Ndehedehe, V. G. Ferreira, and M. J. Kennard, “Machine learning assessment of hydrological model performance under localized water storage changes through downscaling, " J. Hydrol., vol. 628, p. 130597, Jan. 2024, doi: 10.1016/j.jhydrol.2023.130597. [Google Scholar]
  29. A. Laghzal and N. Nouayti, “Contribution to the hydrochemical study of springs Jurassic of the Ziz high basin: Contribution of remote sensing, " J. Mater. Environ. Sci., vol. 9, no. 6, pp. 1889–1898, 2018. [Google Scholar]
  30. L. Bouchaou and J.-L. Michelot, “Contribution des isotopes à l’étude de la recharge des aquifères de la région de Béni Mellal (Tadla, Maroc), " IAHS Publ., vol. 244, pp. 37–44, 1997. [Google Scholar]
  31. K. B. Al-Paruany, S. Al-Naseri, and A.H. F. Al-Ajena, “Distribution of environmental isotopes in the Euphrates River between Qaim-Falluja, western Iraq, " Iraqi Geol. J., pp. 12–27, 2017. [Google Scholar]
  32. A. S. Al-Adili and S. M. Ali, “Hydrochemical Evolution of Shallow Ground Water System Within Baghdad City-Iraq, " Iraqi Geol. J., pp. 134–139, 2005. [Google Scholar]
  33. M. Al-Raggad, S. Al-Harahsheh, M. Ibrahim, A. Al-Shdaifat, and M. Al-Wreikat, “An integrated hydrogeological and remote sensing modeling approach to evaluate the climate change and over-irrigation impact on groundwater depletion in north Jordan, " Iraqi Geol. J., pp. 12–27, 2021. [Google Scholar]
  34. K. El-Fadl and M. El-Fadel, “Comparative assessment of EIA systems in MENA countries: challenges and prospects, " Environ. Impact Assess. Rev., vol. 24, no. 6, pp. 553–593, 2004. [Google Scholar]
  35. L. Taoufiq, M. Chourak, and F. Arrakhiz, “Structural failure of reinforced concrete buildings: The case of Al Haouz earthquake on 8 September 2023, Morocco, " Structures, vol. 108747, Apr. 2025. Available: https://www.sciencedirect.com/science/article/pii/S2352012425005612 [Google Scholar]
  36. Q. Li et al., “Blend sign predicts poor outcome in patients with intracerebral hemorrhage, " PLoS One, vol. 12, no. 8, p. e0183082, 2017. [Google Scholar]
  37. N. Ennaji, H. Ouakhir, S. Halouan, and M. Abahrour, “Assessment of soil erosion rate using the EPM model: case of Ouaoumana basin, Middle Atlas, Morocco, " IOP Conf. Ser.: Earth Environ. Sci., vol. 1090, no. 1, p. 012004, Oct. 2022, doi: 10.1088/17551315/1090/1/012004. [Google Scholar]
  38. S. Baki et al., “Assessment of groundwater intrinsic vulnerability to pollution in the Pre-Saharan areas-the case of the Tafilalet Plain (Southeast Morocco), " Procedia Earth Planet. Sci., vol. 17, pp. 590–593, 2017. [CrossRef] [Google Scholar]
  39. O. Saadi et al., “Application of remote sensing data and geographic information system for identifying potential areas of groundwater storage in middle Moulouya Basin of Morocco,” Groundw. Sustain. Dev., vol. 14, p. 100639, 2021. [CrossRef] [Google Scholar]
  40. T. Mostephaoui et al., “cartographie des risques d’erosion hydrique par l’application de l’equation universelle de pertes en sol a l’aide d’un systeme d’information geographique dans le bassin versant d’el hamel (boussaada) algerie,” J. Algérien Rég. Arides, vol. 12, no. 1, pp. 131–147, 2013. [Google Scholar]
  41. Y. Yu, T. Jia, and X. Chen, "The 'how' and 'where' of plant micro RNAs, " New Phytol., vol. 216, no. 4, pp. 1002–1017, Dec. 2017, doi: 10.1111/nph.14834. [Google Scholar]
  42. K. Oussama, “Cartographie des zones potentielles des eaux souterraines à l'aide du Processus d'analyses hiérarchique AHP, SIG et télédétection dans le bassin versant de Bouhamdane (Nord Est Algérien),” 2024. [Online]. Available: https://dspace.univ-guelma.dz/xmlui/handle/123456789/17024 [Google Scholar]
  43. Y. Wang et al., “A review of regional and Global scale Land Use/Land Cover (LULC) mapping products generated from satellite remote sensing,” ISPRS J. Photogramm. Remote Sens., vol. 206, pp. 311–334, 2023. [Google Scholar]
  44. R. K. Dey, P. Halder, S. Nandy, and R. Ansary, “Identifying Groundwater Potential Zones using Multi-Criteria Approach in Agriculture-Dominated Landscapes of Malda district, India,” Groundw. Sustain. Dev., p. 101497, 202 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.