Advanced Drone Classification Using Light CNN and Image Processing for DJI Models

As the threat from small drones rises, classifying these drones accurately has become increasingly important. DJI (Dà-Jiāng Innovations Science and Technology Co., Ltd.) is a leading manufacturer of such drones, including models like the DJI Inspire 1, DJI Inspire 2, and DJI Spark. To address the growing need for precise drone classification, this study employs image processing and deep learning techniques. Using Light CNN (Convolutional Neural Network) along with advanced image processing methods, we focus on extracting and analyzing images of small drones captured by radar signals. These images are processed to identify and classify drones based on their unique features and patterns. The integration of these technologies allows for accurate differentiation between the DJI Inspire 1, DJI Inspire 2, and DJI Spark models. By leveraging radar data and image processing techniques, the classification system enhances the ability to detect and categorize drones, providing valuable information for security and surveillance purposes. This approach ensures that each drone type can be identified with high precision, aiding in effective monitoring and response strategies. The final classification results, achieved through sophisticated deep learning models, contribute to better understanding and management of the increasing drone threats in various applications.

Keywords: Dataset, Pre-Processing, Convolutional Neural Networks, Deep learning, Classification, Accuracy.