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.

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.

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

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

Detection of Drones using Computer Vision Algorithms

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

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.

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

UAV Object Detection using transfer learning with YOLOv5x

Real-Time Detection of Drones with YOLOv3 Deep Learning Algorithm

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.

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.

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.

Landmine Detection using Drone Camera is an AI-powered drone project designed to enhance safety in mine-affected areas. The system uses a drone equipped with a camera and computer vision algorithms to detect landmines in real-time, allowing operators to safely monitor and avoid hazardous zones.

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.