Introducing a curated dataset for drone detection and a state-of-the-art YOLOv7 model, enabling real-time and accurate identification of drones in complex environments.

This repository provides a dataset and model for real-time drone detection using YOLOv8, contributing to enhanced security and privacy protection. Join us in advancing drone detection technology for safer environments.

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.

TIB-Net: Drone Detection Network With Tiny Iterative Backbone

Detection of Drones using Computer Vision Algorithms

This project provides a trained YOLOv8 model for detecting both multirotor and fixed-wing UAVs (drones) in visual data. Includes example usage and documentation.

From dataset https://universe.roboflow.com/drone-detection-pexej/drone-detection-data-set-yolov7/dataset/1 a model is obtained, based on yolov10 to detect drones in images. Predictions from several models are used in cascade to obtain the optimal result.

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

Real-Time Detection of Drones with YOLOv3 Deep Learning Algorithm

Një model për ti detektuar dronat nga imazhet, videot dhe regjistrimet në kohë reale duke përdorur YOLOv3 dhe PyTorch.

Real-Time Detection of Drones with YOLOv3 Deep Learning Algorithm

UAV Object Detection using transfer learning with YOLOv5x

Drone YOLO Object Detection 📦🛩️ This repository contains a full pipeline for training a YOLOv8 model on custom drone footage data for object detection and line-crossing analysis. The implementation uses the Ultralytics YOLOv8 framework and is tailored for lightweight and fast inference using the YOLOv8 Nano variant.

Drone Project Using Q-Learning : Helping a Drone find a target. Core framework is made to be used with Tello drones, so this algorithm may be compatible with them.

AIegis Beam (formerly known as Mini C-RAM (Counter Rocket, Artillery & Mortar)), the real-time drone detection/tracking system (university capstone project).

YOLOv8 Drone Detection - Lightweight CV model for real-time drone detection.

A neural network that recognizes flying objects, classifies them and plots their trajectory and the vector of their intended movement.

AeroDetect is a real-time object detection project that identifies drones, helicopters, and airplanes in images and videos using a custom-trained YOLOv11n model. The project includes a web interface built with FastAPI that allows users to upload media and visualize detection results instantly.

Development of a hybrid system using YOLOv11 and EKF for drone tracking in inspection scenarios

Real-time drone detection and tracking using YOLOv11x with heatmap visualization. Trained on custom UAV dataset, optimized for small, fast-moving targets.