Integration of CNN Model to Analyze UAV-based Collected Data in Agricultural Land Surveillance
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Abstract
This study explored the integration of convolutional neural network (CNN) models in analyzing unmanned aerial vehicle (UAV)-collected data for agricultural land surveillance. UAV technology has become widely used in agriculture for monitoring crop conditions, detecting plant health issues, and improving agricultural productivity. However, the large volume of image data captured through UAV sensors requires advanced analytical techniques for accurate interpretation. The study examined deep learning methods, particularly CNN-based models, to classify crops and analyze agricultural land characteristics. Results demonstrate that …
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Cite This Research
R Tabiongan, M Labrador (2022). Integration of CNN Model to Analyze UAV-based Collected Data in Agricultural Land Surveillance. College of Engineering, Samar State University. Retrieved from https://gov-aideas.ssu.edu.ph/research/integration-of-cnn-model-to-analyze-uav-based-collected-data-in-agricultural-land-surveillance
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Research Information
- Research Type
- Applied Research
- Sector
- Science, Technology & Innovation
- College
- College of Engineering
- Published
- March 06, 2026
- Last Updated
- March 06, 2026
- Access Level
- Public
- File Size
- 9.5 MB