Yildiran, S. TolgaYanikoglu, BerrinAbdullah, Erhan2024-10-152024-10-152014097814799487412165-0608[WOS-DOI-BELIRLENECEK-175]https://hdl.handle.net/20.500.14517/6413Yanikoglu, Berrin/0000-0001-7403-7592We present a plant image recognition system geared towards plants with flowers. The system uses local invariants with Dense SIFT features and Bag of Visual Words representation, while the classification is done using Support Vector Machines. Our approach contains a pre-classification stage where images are categorized into color subgroups, to reduce the complexity of the problem. Using a 161-class subset of the ImageClef'2013 flower dataset, the classification accuracy is measured as %42.68, compared to %18 eithout the pre-classification.trinfo:eu-repo/semantics/closedAccessDense SIFT K Means ClusteringBag of Visual Words (BOVW)SVMsPHOWConference Object20942097WOS:000356351400503