Year: 2025
Type: article
Abstract: The feature extraction-based IDRONE project focuses on leveraging computer vision and deep learning to identify and analyze key environmental features from aerial data. Unlike traditional drones that rely solely on navigation, this system is designed to capture, process, and extract meaningful insights from real-time images and sensor data. Equipped with high-resolution cameras, LiDAR, and IMU sensors, the drone collects raw data, which is then processed using advanced feature extraction algorithms such as edge detection, key point matching, and deep learning-based object recognition. This enables accurate terrain analysis, object detection, and environmental monitoring. The extracted features can be applied in disaster assessment, precision agriculture, infrastructure monitoring, and autonomous mapping. By optimizing onboard AI processing and real-time analytics, this system enhances data-driven decision-making, making IDRONE a powerful tool for automated feature recognition and analysis in aerial applications.
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410097810