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1تقرير
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2دورية أكاديمية
المؤلفون: Nogueira, Keiller, Machado, Gabriel L S, Gama, Pedro H T, Da Silva, Caio C V, Balaniuk, Remis, Santos, Jefersson A Dos
المساهمون: Brazilian National Research Council, Computing Science, Federal University of Minas Gerais, Universidade Católica de Brasília, orcid:0000-0003-3308-6384
مصطلحات موضوعية: Deep Learning, Remote Sensing, Erosion Identification, High-Resolution Images 14
وصف الملف: application/pdf
العلاقة: Nogueira K, Machado GLS, Gama PHT, Da Silva CCV, Balaniuk R & Santos JAD (2020) Facing Erosion Identification in Railway Lines Using Pixel-wise Deep-based Approaches. Remote Sensing , 12 (4), Art. No.: 739. https://doi.org/10.3390/rs12040739Test; 739; http://hdl.handle.net/1893/30819Test; WOS:000519564600150; 2-s2.0-85080927654; 1557136; http://dspace.stir.ac.uk/bitstream/1893/30819/1/remotesensing-12-00739.pdfTest
الإتاحة: https://doi.org/10.3390/rs12040739Test
http://hdl.handle.net/1893/30819Test
http://dspace.stir.ac.uk/bitstream/1893/30819/1/remotesensing-12-00739.pdfTest -
3مؤتمر
المساهمون: Brazilian National Research Council, Federal University of Minas Gerais, Computing Science, orcid:0000-0003-3308-6384, orcid:0000-0002-8889-1586
مصطلحات موضوعية: Open Set, Deep Learning, Semantic Segmentation, Remote Sensing
وصف الملف: application/pdf
العلاقة: da Silva CCV, Nogueira K, Oliveira HN & dos Santos JA (2020) Towards Open-Set Semantic Segmentation of Aerial Images. In: 2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 . IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS 2020), Santiago, Chile, 21.03.2020-26.03.2020. Piscataway, NJ, USA: Institute of Electrical and Electronics Engineers Inc. pp. 16-21. https://doi.org/10.1109/LAGIRS48042.2020.9165597Test; http://hdl.handle.net/1893/31891Test; 2-s2.0-85091623257; 1669741; http://dspace.stir.ac.uk/bitstream/1893/31891/1/Towards_Open-Set_Semantic_Segmentation_of_Aerial_I.pdfTest
الإتاحة: https://doi.org/10.1109/LAGIRS48042.2020.9165597Test
http://hdl.handle.net/1893/31891Test
http://dspace.stir.ac.uk/bitstream/1893/31891/1/Towards_Open-Set_Semantic_Segmentation_of_Aerial_I.pdfTest