● batear — Ultra-low-cost, off-grid acoustic drone detector. Edge computing. Protect your airspace with a microphone.

Multi-protocol SDR signal detection and triangulation system for ATAK. Detects radio emissions from distributed receivers using RTL-SDR and HackRF.

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.

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

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

🔇 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.

Detection of Drones using Computer Vision Algorithms

Situational awareness platform for distributed counter-surveillance sensors over LoRa mesh.

GhostBLE is a BLE privacy scanner for the M5Stack Cardputer. It discovers nearby devices, analyzes their privacy posture, and visualizes BLE activity with the interactive mascot Nibbles.

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.

Multi-band passive drone detector on ESP32 | Мультидиапазонный детектор БПЛА | 900MHz/2.4GHz/5.8GHz RF scanner with countermeasures

UAV Object Detection using transfer learning with YOLOv5x

YOLOv8-based drone detection model for real-time identification of drones, UAVs, birds, and airplanes. Developed after the 12-day Iran-Israel conflict to enhance aerial threat monitoring.

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.

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.