Development of a Machine Learning method for Detecting objects of military  equipment on drone footage

dc.contributor.author	Hutsul, Danyil
dc.date.accessioned	2024-02-14T08:28:28Z
dc.date.available	2024-02-14T08:28:28Z
dc.date.issued	2023
dc.identifier.citation	Hutsul, Danyil. Development of a Machine Learning method for Detecting objects of military equipment on drone footage / Danyil Hutsul; Supervisor: Oles Dobosevych; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2023. – 31 p.: ill.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4388
dc.language.iso	en	uk
dc.title	Development of a Machine Learning method for Detecting objects of military equipment on drone footage	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Visual object detection is one of the most common research topics in the sphere of computer vision research. It has a vast range of areas of application, from medical to automotive. One such area is the detection of objects from videos and images taken by unmanned aerial vehicles for both military and civilian purposes. With the start of the latest phase of the Russo-Ukranian war, a great number of videos, taken both military-grade and repurposed civilian drones, have begun appearing all over the internet. In this paper, we collect a number of such videos to create a dataset and train several object detection models with the goal of finding one best suited for the task. The code used in this paper is available on GitHub.	uk