This is official repository of our paper "RFUAV: A Benchmark Dataset for Unmanned Aerial Vehicle Detection and Identification". Codes include a two stage model to achieve drone detection and classification using some FFT/STFT analytical method. The Raw data will be free to use after our paper is accept. Star us!!!!, if you think this is useful♥

Drone / Unmanned Aerial Vehicle (UAV) Detection is a very safety critical project. It takes in Infrared (IR) video streams and detects drones in it with high accuracy.

Real Time Drone Detection with YOLOv3, YOLOv3-tiny, YOLOv4, YOLOv4-tiny, YOLOv5x, YOLOv5s, YOLOv6-L, YOLOv6-S, YOLOv7-X, YOLOv7, YOLOv8l and YOLOv8s

Advanced radar-based classification system for detecting and distinguishing UAVs, birds, and RC aircraft using SVMD signal decomposition and deep learning feature extraction.

Marker-less UAV detection project.

Leader-Follower-Based Collaborative Navigation of a UGV-UAV Formation

UAV Object Detection using transfer learning with YOLOv5x

Real-Time Detection of Drones with YOLOv3 Deep Learning Algorithm

UAV tracking algorithm and PID controller for 2 axis gimbal mechanism

Real-Time Detection of Drones with YOLOv3 Deep Learning Algorithm

🔇 A production-grade deep learning system for real-time drone/UAV detection through acoustic signature analysis. Converts raw audio to Mel-Spectrograms and classifies using a custom CNN. Features auto-dataset ingestion, defense-optimized metrics (high recall), early stopping, model checkpointing, and a ready-to-use inference API.

LUPI-OD - A novel methodology to improve object detection accuracy without increasing model size or complexity. | 2025 European Workshop on Visual Information Processing (EUVIP) | M.Sc. ICT (By Research) Dissertation | University of Malta

Thermal image datasets of UAVs taken from UAV

"Code from Hands-On Simulation Modeling with Python - Second Edition by Packt, focusing on simulation models for efficient decision-making."

This project is a Python-based GPS spoofing detection tool designed to analyze and detect anomalies in GPS data, which is a crucial step toward defending against malicious interference with Unmanned Aerial Systems (UAS). Initially built for dataset-based detection, this tool will evolve into a specialized weapon in the COUNTER-UAS (C-UAS) arsenal

Enhanced Aerial Object Detection for Aviation (99.4% mAP) — IIIT Hyderabad Computer Vision Internship 2025-26

Official implementation of Context-Aware Data Augmentation for Small UAV Detection.

Drone Detection-Tracking-and-Payload-Identification Challenge