title: Drone detection system application
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¾Ð±Ð½Ð°ÑÑÐ¶ÐµÐ½Ð¸Ñ Ð±ÐµÑÐ¿Ð¸Ð»Ð¾ÑÐ½ÑÑ Ð»ÐµÑÐ°ÑÐµÐ»ÑÐ½ÑÑ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ¾Ð²
Creators: name: ÐÐ¸ÐºÐ¸ÑÐ¾ÑÐ¾Ð², Ð¢Ð¸Ð¼Ð¾ÑÐµÐ¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÐÐµÑÐ°ÑÐµÐ»ÑÐ½ÑÐµ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÑ Ð±ÐµÑÐ¿Ð¸Ð»Ð¾ÑÐ½ÑÐµ
software development
graphical user interface
ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ
Ð³ÑÐ°ÑÐ¸ÑÐµÑÐºÐ¸Ð¹ Ð¸Ð½ÑÐµÑÑÐµÐ¹Ñ Ð¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°ÑÐµÐ»Ñ

description: This work examines existing developments and proposes proprietary solutions in the field of unmanned aerial vehicle (UAV) detection in images using neural network algorithms and digital image processing techniques. The first section of the work provides a description of the goal and objectives of the final product, a review of existing commercial solutions and publications in the relevant field, as well as a justification for selecting a set of tools and libraries for solving the task. The second section of the paper is a theoretical exploration of issues related to criteria for comparing models, methods for addressing detection and classification problems, and the implementation of a graphical application. It also presents a novel approach to classifying UAVs based on their cargo. The VGG16 and YOLOv8 architectures were selected as neural network-based solutions for this task, Haar Cascades and SIFT algorithms were used to address the problem using digital image processing techniques. The third section of the work describes the overall scheme of the application under development and the code that implements the selected algorithms and graphical interface; the described flowcharts and code are located within the application section. In the final section of the paper, a comparison of the implemented algorithms is presented, and the most suitable combinations of algorithms are selected, depending on the specific task at hand: processing an image stream, achieving maximum processing speed, or achieving maximum accuracy. Finally, a discussion of possible future enhancements to the project within the context of this thesis work is provided.
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