دانلود مقاله انگلیسی رایگان:یک روش یادگیری ماشین تطبیقی برای بهبود تشخیص خودکار کوه یخ از تصاویر SAR - 2019
بلافاصله پس از پرداخت دانلود کنید
دانلود مقاله انگلیسی یادگیری ماشین رایگان
  • An adaptive machine learning approach to improve automatic iceberg detection from SAR images An adaptive machine learning approach to improve automatic iceberg detection from SAR images
    An adaptive machine learning approach to improve automatic iceberg detection from SAR images

    سال انتشار:

    2019


    عنوان انگلیسی مقاله:

    An adaptive machine learning approach to improve automatic iceberg detection from SAR images


    ترجمه فارسی عنوان مقاله:

    یک روش یادگیری ماشین تطبیقی برای بهبود تشخیص خودکار کوه یخ از تصاویر SAR


    منبع:

    Sciencedirect - Elsevier - ISPRS Journal of Photogrammetry and Remote Sensing, 156 (2019) 247-259: doi:10:1016/j:isprsjprs:2019:08:015


    نویسنده:

    Mauro M. Barbata,⁎, Christine Weschec, Adriano V. Werhlib, Mauricio M. Mataa


    چکیده انگلیسی:

    Iceberg distribution, dispersion and melting patterns are fundamental aspects in the balance of heat and freshwater in the Southern Ocean; yet these features are not fully understood. This lack of understanding is, in part, due to the difficulties in accurately identifying icebergs in different environmental conditions. To improve the understanding, reliable iceberg detection tools are necessary to achieve a detailed picture of iceberg drift and disintegration patterns, an thus to gain further information on the freshwater input into the Southern Ocean. Here, we present an accurate automatic large-scale iceberg detection method using an alternative machine learning architecture applied to high resolution Synthetic Aperture Radar (SAR) images. Our method is based on the concept of adaptability and focuses on improving the performance of identifying icebergs in ambiguous environmental contexts with wide radiometric, textural, size and shape variability. The fundamentals of the method are centred on superpixel segmentation, ensemble learning and incremental learning. The method is applied to a dataset containing 586 ENVISAT Advanced SAR images acquired during 2003–2005 (Weddell Sea region) and to the Radarsat-1 Antarctic Mapping Project (RAMP) mosaic, covering the Antarctic wide nearcoastal zone. These images cover scenes under heterogenous backscattering signatures for all seasons with variable meteorological, oceanographic and acquisition parameters (e.g. band, polarization). Our method is highly adaptable to distinguish icebergs from ambiguous objects hidden in the images. The average false positive rate and miss rate are 2.3 ± 0.4% and 3.3 ± 0.4%, respectively. Overall, 9512 icebergs with sizes varying from 0.1 to 4567.82 km2 are detected with average classification accuracy of 97.5 ± 0.6%. The results confirm that the method presented here is robust for widespread iceberg detection in the Antarctic seas.
    Keywords: Icebergs | Detection | SAR | Southern Ocean | Machine learning


    سطح: متوسط
    تعداد صفحات فایل pdf انگلیسی: 13
    حجم فایل: 9832 کیلوبایت

    قیمت: رایگان


    توضیحات اضافی:




اگر این مقاله را پسندیدید آن را در شبکه های اجتماعی به اشتراک بگذارید (برای به اشتراک گذاری بر روی ایکن های زیر کلیک کنید)

تعداد نظرات : 0

الزامی
الزامی
الزامی
rss مقالات ترجمه شده rss مقالات انگلیسی rss کتاب های انگلیسی rss مقالات آموزشی