How to Create AI Segmentation Datasets from Satellite Imagery скачать в хорошем качестве

How to Create AI Segmentation Datasets from Satellite Imagery

In this tutorial I show how to generate AI segmentation training datasets directly from satellite imagery using MinerAI. Traditionally, building geospatial AI datasets requires multiple tools: Download satellite imagery from providers Annotate images on a labeling platform Generate segmentation masks using custom scripts Prepare the dataset for model training This workflow is slow, complex, and error-prone. With MinerAI, the entire pipeline happens in one place. You can: • Draw annotations directly on satellite maps • Automatically generate segmentation masks • Export perfectly aligned images and masks • Download ready-to-train datasets in minutes Instead of spending hours collecting and preparing satellite data, MinerAI turns maps into AI training datasets instantly. Try MinerAI https://minerai.space What you will learn in this video • How to annotate satellite imagery for AI training • How to export segmentation datasets from maps • How MinerAI generates masks automatically • How to download datasets ready for model training Use cases MinerAI can be used to build AI datasets for: • Mining detection • Deforestation monitoring • Land use analysis • Environmental monitoring • Construction detection • Agriculture analysis Keywords geospatial ai satellite imagery ai segmentation dataset remote sensing machine learning satellite image annotation computer vision datasets ai dataset generation geospatial machine learning About MinerAI MinerAI is a geospatial AI platform that allows researchers, engineers, and organizations to generate satellite datasets, train segmentation models, and deploy geospatial AI systems. The goal is to dramatically reduce the time required to build geospatial AI pipelines. If you're building geospatial AI models and need datasets from satellite imagery, try MinerAI → https://minerai.space