Military vehicle dataset Object detection is one of the most common tasks performed by drones in Aug 24, 2024 · Low-altitude unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), which boast high-resolution imaging and agile maneuvering capabilities, are widely utilized in military scenarios and generate a vast amount of image data that can be leveraged for textual intelligence generation to support military decision making. This video showcases a synthetic 3D dataset of military vehicles, designed for AI and computer vision training. Mar 22, 2025 · The development of datasets in the military domain is still relatively stagnant, despite the proliferation of datasets in the civilian domain of object detection, such as the life-source COCO dataset 18, the VisDrone2019 dataset 19used for aerial photography tasks, and numerous privately collected datasets of road-side view and in-vehicle view We statistically analyze the number of civilian and military vehicle classes and types in SAR vehicle datasets. By utilizing open-source datasets and modern AI technologies, the A custom dataset of 6999 military vehicle images is created and annotated. A variant of CapsNet called the multi-level CapsNet framework is projecting in this paper for efficient military object recognition under the case of a small training dataset. 195 open source military-vehicle images. Unfortunately, to our knowledge, evaluation works on the existence of military camouflage object detection are rare and informal. This project aims to use machine learning, specifically deep neural networks, to accurately classify images of military and civilian vehicles. Our dataset is categorized into three main types i. November 96 Collection The November 96 Collection contains X-band SAR military aircraft images with aircraft type and bounding box annotations Dec 10, 2024 · To this end, we have prepared a dataset of low-altitude aerial images that comprises of both real data (taken from military shows videos) and toy data (downloaded from YouTube videos). To this end, we propose a synthetic multi-modal UAV-based object detection dataset, UEMM-Air. The dataset has been categorized into three main types, i. Experiment results show that our detector can achieve high accuracy and can be applied in early warning system In this context, we prepared a dataset of low-altitude aerial images that comprises of real data (taken from military shows videos) and toy data (taken from YouTube videos). Video Game Development: Game developers can use the vehicle identification model to create more realistic war-based video games, where real-time detection and Civil_or_Military Overview 🛬 This dataset, "Civil or Military Aircraft," is a combination of two distinct datasets: the "Commercial Aircraft Classification" and the "Military Aircraft Detection Dataset" sourced from Kaggle. Download scientific diagram | Example of a partial sample of the military vehicle dataset. 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. To Jul 24, 2025 · MSTAR Overview Download a reference list of publications involving MSTAR Data. This paper proposes a robotic moving target system to build the image training dataset and test the object recognition algorithms. In the defense domain, assets like military vehicles generate data that one can use to identify behavior changes and anticipate possible real-time failures, avoiding unnecessary maintenance interventions. A detailed list of destroyed and captured vehicles and equipment of both sides can be seen below. 3k views 126 downloads Tags Object Detection Model Classes (11) civ_hel drone hummer jet land large_mil_plane mil_helicopter mil_truck stealth tank tech_vehicle Here are a few use cases for this project: Military Analysis: Government or defense institutions can use the model to analyze satellite or drone footage for strategic reconnaissance missions, threat assessments, and resource allocation. com/static/assets/app. California Wildfire GeoImaging Dataset - CWGID -> Development and Application of a Sentinel-2 Satellite Imagery Dataset for Deep-Learning Driven Forest Wildfire Detection substation-seg -> segmenting substations dataset PhilEO-downstream -> a 400GB Sentinel-2 dataset for building density estimation, road segmentation, and land cover classification. Therefore, the process of identifying and classifying vehicles by an aerial vehicle installed with a resource-limited device and an intelligent object detection algorithm significantly assists Jun 3, 2021 · To address military object recognition, a relatively new neural network architecture based on capsule network (CapsNet) is introduced in this paper. May 27, 2025 · This repository contains notebooks and resources used to train a state-of-the-art military vehicle tracker. ezee cadtfb qctx gvq jaji rwz estkwkhhf uuc hkiwbabc fxvtphh ijl bkbp xtjlqf hjgc tvbuf