Military Vehicle Recognition Computer Vision Project

0

views

0

downloads
Classes (5)
air-fighter
armoured personnel carrier
bomber
soldier
tank

Metrics

Try This Model
Drop an image or
Description

This dataset contains labeled aerial images of air fighters, bombers, armored personnel carriers, tanks and soldiers captured by reconnaissance drones during the russo-Ukrainian War, aimed at supporting the development of machine learning models for military object detection. The images simulate real-world conditions with diverse altitudes, angles, and lighting, providing a robust foundation for applications in automated surveillance and situational awareness. Ideal for defense and security contexts, this dataset enables precise detection and classification of military objects, aiding in real-time decision-making and enhancing overall reconnaissance capabilities.

Use This Trained Model

Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.

Supervision

Build Computer Vision Applications Faster with Supervision

Visualize and process your model results with our reusable computer vision tools.

Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            military-vehicle-recognition_dataset,
                            title = { Military Vehicle Recognition Dataset },
                            type = { Open Source Dataset },
                            author = { MilitaryVehicleRecognition },
                            howpublished = { \url{ https://universe.roboflow.com/militaryvehiclerecognition/military-vehicle-recognition } },
                            url = { https://universe.roboflow.com/militaryvehiclerecognition/military-vehicle-recognition },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { nov },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

Similar Projects

See More