Transfer Learning Methods for Training Person Detector in Drone Imagery (CROSBI ID 712106)
Prilog sa skupa u časopisu | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Sambolek, Saša ; Ivasic-Kos, Marina
engleski
Transfer Learning Methods for Training Person Detector in Drone Imagery
Deep neural networks achieve excellent results on various computer vision tasks, but learning models require large amounts of tagged images and often unavailable data. An alternative solution of using a large amount of data to achieve better results and greater generalization of the model is to use previously learned models and adapt them to the task at hand, known as transfer learning. The aim of this paper is to improve the results of detecting people in search and rescue scenes using YOLOv4 detectors. Since the original SARD data set for training human detectors in search and rescue scenes are modest, different transfer learning approaches are analyzed. Additionally, the VisDrone data set containing drone images in urban areas is used to increase training data in order to improve person detection results.
Transfer learning ; YOLO v4 ; Person detection ; Drone dataset
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Podaci o prilogu
688-701.
2022.
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objavljeno
10.1007/978-3-030-82196-8_51
Podaci o matičnoj publikaciji
Lecture notes in networks and systems
Arai, Kohei
Springer
978-3-030-82195-1
2367-3370
2367-3389
Podaci o skupu
Nepoznat skup
predavanje
29.02.1904-29.02.2096
Povezanost rada
Informacijske i komunikacijske znanosti, Računarstvo