Drone Detection and Classification using Deep Learning
Dinesh Behera, Arockia Bazil Raj
Abstract
This paper presents a systematic approach to drone detection and classification using deep learning with different modalities. The YOLOv3 object detector is used to detect the moving or still objects. It uses a computer vision-based approach as a reliable solution. The convolutional neural network helps to extract features from images and to detect the object with maximum accuracy. The model is trained with a proper dataset and trained for 150 epoch only to detect various types of drones. A convolutional neural network with modern object detection methods shows an excellent approach for real-time detection of drones.
Topics & Concepts
Convolutional neural networkArtificial intelligenceComputer scienceDroneObject detectionDeep learningDetectorObject (grammar)Computer visionPattern recognition (psychology)TelecommunicationsGeneticsBiologyAdvanced Neural Network ApplicationsVideo Surveillance and Tracking MethodsUAV Applications and Optimization