SVM-Based Fuzzy Decision Trees for Classification of High Spatial Resolution Remote Sensing Images

By Serafeim P. Moustakidis, Giorgos Mallinis, Nikos Koutsias, Ioannis B. Theocharis, Vassilios Petridis. 2012

119 citations recorded by the source corpus.

Subfields: Atmospheric Science, Computer Vision and Pattern Recognition, Ecology, Media Technology, Remote Sensing

Citations in the corpus

• A Survey on Object Detection in Optical Remote Sensing Images (2016, unknown): “…Stankov and He, 2013, 2014; Wegner et al., 2011a; Wegner et al., 2011b), trees (Haala and Brenner, 1999; Hung et al., 2012; Malek et al., 2014; Moustakidis et al., 2012; Yang et al., 2013), vehicles (Eikvil et al., 2009; Grabner et al., 2008; Jin and Davis, 2007; Kembhavi et al., 2011;…”
• Strathprints Institutional Repository Shuhui and Ren, Jinchang (2015) Effective and Efficient Midlevel Visual Elements-oriented Land-use Classification Using Vhr Remote Sensing Images. Ieee Transactions on Geoscience and Remote Sensing, 53 (8). Pp. 4238-4249. Issn 0196-2892 Effective and Efficient M (unknown): “Most previous works [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] mainly focus on classifying pixels or objects (or rather, grouping of local homogeneous pixels) into their thematic class by extracting low-level image features (e.g. texture feature [9] [10], color feature [8], spatial and…”