BENCHMARK OF MACHINE LEARNING METHODS FOR CLASSIFICATION OF A SENTINEL-2 IMAGE

Pirotti F., Sunar F., Piragnolo M.

23rd Congress of the International-Society-for-Photogrammetry-and-Remote-Sensing (ISPRS), Prague, Çek Cumhuriyeti, 12 - 19 Temmuz 2016, cilt.41, ss.335-340 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 41
  • Doi Numarası: 10.5194/isprsarchives-xli-b7-335-2016
  • Basıldığı Şehir: Prague
  • Basıldığı Ülke: Çek Cumhuriyeti
  • Sayfa Sayıları: ss.335-340
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Thanks to mainly ESA and USGS, a large bulk of free images of the Earth is readily available nowadays. One of the main goals of remote sensing is to label images according to a set of semantic categories, i.e. image classification. This is a very challenging issue since land cover of a specific class may present a large spatial and spectral variability and objects may appear at different scales and orientations.