ENVI Deep Learning is an add-on module for the ENVI platform that brings modern neural network–based analytics to remote sensing and geospatial imagery. It enables you to create labeled training data, train models for semantic segmentation and object detection, and run inference to locate and classify features—such as buildings, roads, vegetation, or change—across large scenes.
The module supports a wide range of imagery types, including multispectral and hyperspectral data, and takes advantage of GPU acceleration where available to speed up training and production workflows. Guided tools walk you through data preparation, augmentation, training, validation, and accuracy assessment, helping you build robust models with less trial and error.
Outputs integrate seamlessly with ENVI, allowing you to combine deep learning with traditional image processing, automate tasks in ENVI Modeler or via the API, and export results as rasters, vector features, or reports. Designed for analysts and scientists, ENVI Deep Learning streamlines the path from labeled samples to operational products, making it easier to map, monitor, and derive insight from complex imagery at scale.
ENVI Deep Learning is developed by Harris Geospatial Solutions, Inc.. The most popular versions of this product among our users are: 1.1 and 3.0.
You can check Deep Freeze Standard, Deep Exploration, Deep Fritz DL and other related programs like Deep Voyage at the "download" section.
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