● 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.

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

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.

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.