BENEFITS & FEATURES

Key Benefits:

• Assisted and accelerated feature extraction (AFE)
• Multi-class and single-class feature collection with spatial context
• Change detection
• Batch processing
• Learning models
• Hierarchical learning for clutter removal
• Unsupervised classification
• Auto-attribution of 3D features using shape metrics
• Image and data fusion
• Small feature and wall-to-wall extraction capability
• Image processing tools
• Vector and raster conversion
• Advanced vector clean-up for lines, polygons, and intersections
• Square-up features
• Convert to line with gap jumping
• Convert to point
• Smoothing algorithms for lines and polygons
• Complete tutorial and technical training

Technical Features:

• Suite of machine learning algorithms "learn" how to classify the object-specific geographic features specified by the user
• Hierarchical learning for adaptive feature extraction to identify objects in complex and cluttered scenes iteratively improve classification
• Ability to use spatial context when extracting features
• Adaptive user interface hides the complexity of the underlying machine learning system from the average GIS user
• Clutter removal allows users to clean up their results even beyond hierarchical learning
• Uses image characteristics, such as color, size, shape, texture, pattern, shadow, and spatial association, for feature classification
• Learning library for importing and exporting learning models for user-specified geographic feature classes and published data models
• API for developing third-party solutions