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.

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.

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.

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

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

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 Detection Project made with Detectron2

Autonomous detection of people using overhead drones and taking count, sending location details, to be used for rescue during disasters