Please use this identifier to cite or link to this item:
https://hdl.handle.net/11147/14387
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yılmaz,C. | - |
dc.contributor.author | Ozgun,A. | - |
dc.contributor.author | Erol,B.A. | - |
dc.contributor.author | Gumus,A. | - |
dc.date.accessioned | 2024-05-05T14:57:10Z | - |
dc.date.available | 2024-05-05T14:57:10Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 978-303152759-3 | - |
dc.identifier.issn | 2522-8595 | - |
dc.identifier.uri | https://doi.org/10.1007/978-3-031-52760-9_11 | - |
dc.identifier.uri | https://hdl.handle.net/11147/14387 | - |
dc.description.abstract | This work presents an investigation into the domain of dynamic target tracking through object detection, particularly emphasizing the context of open-source applications like PX4, ROS, and YOLO. Over the years, achieving real-time object tracking on UAVs in dynamic environments has been a formidable challenge, necessitating offline computations or substantial onboard processing resources. However, contemporary UAVs are now equipped with advanced edge embedded devices, sensors, and cameras, enabling the integration of deep learning-based vision applications. This advancement offers the prospect of directly deploying cutting-edge applications onto UAVs, thereby expanding their utility in areas such as surveillance, search and rescue, and videography. To fully harness the potential of these vision applications, a communication infrastructure interfacing with the UAV’s underneath closed controllers becomes imperative. We’ve developed an integrated visual target-tracking system that connects a flight controller unit with a graphical unit by leveraging ROS tools and open-source deep learning packages. The overall integrated system based on ROS, deep learning applications, and custom PID controllers is shared on GitHub as open-source software package in a way that benefits everyone interested: https://github.com/miralab-ai/vision-ROS. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Science and Business Media Deutschland GmbH | en_US |
dc.relation.ispartof | EAI/Springer Innovations in Communication and Computing -- 2nd International Congress of Electrical and Computer Engineering, ICECENG 2023 -- 22 November 2023 through 25 November 2023 -- Bandirma -- 309799 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Computer Vision | en_US |
dc.subject | ROS | en_US |
dc.subject | Sim2Real | en_US |
dc.subject | UAV | en_US |
dc.subject | Visual Target Tracking | en_US |
dc.subject | YOLOv7-Tiny | en_US |
dc.title | Open-Source Visual Target-Tracking System Both on Simulation Environment and Real Unmanned Aerial Vehicles | en_US |
dc.type | Conference Object | en_US |
dc.department | Izmir Institute of Technology | en_US |
dc.identifier.startpage | 147 | en_US |
dc.identifier.endpage | 159 | en_US |
dc.identifier.scopus | 2-s2.0-85189545876 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
dc.identifier.doi | 10.1007/978-3-031-52760-9_11 | - |
dc.authorscopusid | 58972527100 | - |
dc.authorscopusid | 58971888200 | - |
dc.authorscopusid | 56825414300 | - |
dc.authorscopusid | 35315599800 | - |
dc.identifier.wosquality | N/A | - |
dc.identifier.scopusquality | Q3 | - |
item.grantfulltext | none | - |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
Appears in Collections: | Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection |
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