Drone design for object detection using YOLOv8

Yamalakonda, Venu Gopal

Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/16421

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DC Field	Value	Language
dc.contributor.author	Yamalakonda, Venu Gopal	en_US
dc.date.accessioned	2025-07-09T13:48:01Z	-
dc.date.available	2025-07-09T13:48:01Z	-
dc.date.issued	2025	-
dc.identifier.citation	Prakash, P., Yamalakonda, V. G., & Singh, A. K. (2025). Drone design for object detection using YOLOv8. ICE 2025 - International Conference on Innovation in Computing and Engineering. https://doi.org/10.1109/ICE63309.2025.10984333	en_US
dc.identifier.other	EID(2-s2.0-105008498701)	-
dc.identifier.uri	https://dx.doi.org/10.1109/ICE63309.2025.10984333	-
dc.identifier.uri	https://dspace.iiti.ac.in:8080/jspui/handle/123456789/16421	-
dc.description.abstract	In this ongoing work, we have designed a drone that is controlled by a wireless transmitter, utilizing the Pixhawk flight controller to ensure smooth and stable flight operations. Additionally, the drone features a camera for capturing aerial images and videos. The custom-built drone is capable of flying and detecting objects through a camera frame. We have incorporated the powerful YOLOv8 object detection algorithm for accurate object detection. The final results showcase drone-based object detection with high accuracy in milliseconds. © 2025 IEEE.	en_US
dc.language.iso	en	en_US
dc.publisher	Institute of Electrical and Electronics Engineers Inc.	en_US
dc.source	ICE 2025 - International Conference on Innovation in Computing and Engineering	en_US
dc.subject	Drone-based object detection	en_US
dc.subject	Hexacopter development	en_US
dc.subject	YOLOv8 (You Only Look Once)	en_US
dc.title	Drone design for object detection using YOLOv8	en_US
dc.type	Conference Paper	en_US
Appears in Collections:	Department of Electrical Engineering

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