Performance Analysis of YOLOv7 and YOLOv8 Models for Drone Detection
- Title
- Performance Analysis of YOLOv7 and YOLOv8 Models for Drone Detection
- Creator
- Agarwal K.; Ashik Sanyo M.S.; Bakshi S.; Vinay M.; Jayapriya J.; Deepa S.
- Description
- Drone detection techniques are used to detect unmanned aerial systems (UAS) also commonly known as drones. A rapid increase in these drones has limited the airspace safety and so the research for drone detection has emerged. This study compares between the two widely used deep-learning models, previously used YOLOv7 and the latest YOLOv8. The overall finding of this study suggests that the YOLOv8 deep-learning model appears to be more promising and may make valuable contributions on their own. We got the result that for 10 epochs YOLOv8 gave 50.16% accuracy while YOLOv7 gave 48.16% accuracy making YOLOv8 more promising for the task. As a practical application for future work, we intend to deploy YOLOv8 on edge devices to achieve real-time drone detection in critical security applications. 2023 IEEE.
- Source
- 2023 International Conference on Network, Multimedia and Information Technology, NMITCON 2023
- Date
- 2023-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- CNN (convoluted neural network); Computer Vision; Drone Detection; UAS (Unmanned Aerial System); unmanned aerial vehicles (UAVs); Yolo (You Only Look Once); Yolov7; Yolov8
- Coverage
- Agarwal K., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Ashik Sanyo M.S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Bakshi S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Vinay M., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Jayapriya J., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India; Deepa S., Christ Universtiy, Department Computer Science, Karnataka, Bangalore, India
- Rights
- Restricted Access
- Relation
- ISBN: 979-835030082-6
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Agarwal K.; Ashik Sanyo M.S.; Bakshi S.; Vinay M.; Jayapriya J.; Deepa S., “Performance Analysis of YOLOv7 and YOLOv8 Models for Drone Detection,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19793.