Turkoglu, MuammerUzen, HuseyinHanbay, Davut2024-08-042024-08-042020978-1-7281-7206-42165-0608https://hdl.handle.net/11616/10218428th Signal Processing and Communications Applications Conference (SIU) -- OCT 05-07, 2020 -- ELECTR NETWORKIn this study, a convolutional neural network (ESA) based feature extracting hybrid model was proposed for the identification of bees carrying pollen or not. The fc6 and fc7 layers of AlexNet and VGG16 which a pre-trained ESA architecture, were used as feature extractors. The performances of the different combinations of the deep properties obtained using the SVM classifier were calculated. The PollenDataset dataset was used to test the proposed model. According to the experimental results, an accuracy score of 97.20% was obtained. As a result, the obtained accuracy score was compared with the state-of-the-art accuracy scores and the proposed model provided better performance than the compared methods.trinfo:eu-repo/semantics/closedAccessObject recognitionConvolutional Neural NetworksAlexNet architectureVGG16 architectureSVM classifierConference ObjectWOS:000653136100341N/A