Classification Efficiency of Pre-Trained Deep CNN Models on Camera Trap Images (CROSBI ID 304473)
Prilog u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Stančić, Adam ; Vyroubal, Vedran ; Slijepčević, Vedran
engleski
Classification Efficiency of Pre-Trained Deep CNN Models on Camera Trap Images
This paper presents the evaluation of 36 convolutional neural network (CNN) models, which were trained on the same dataset (ImageNet). The aim of this research was to evaluate the performance of pre-trained models on the binary classification of images in a “real-world” application. The classification of wildlife images was the use case, in particular, those of the Eurasian lynx (lat. “Lynx lynx”), which were collected by camera traps in various locations in Croatia. The collected images varied greatly in terms of image quality, while the dataset itself was highly imbalanced in terms of the percentage of images that depicted lynxes.
classification ; CNN ; efficiency ; pre-trained ; camera trap
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Podaci o izdanju
Trošak objave rada u otvorenom pristupu
Povezanost rada
Interdisciplinarne tehničke znanosti, Računarstvo