DATA ANNOTATION FOR AERIAL IMAGING
Keymakr creates high quality training data for your computer vision models. We annotate and label aerial images and videos with various techniques:



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Common use cases of computer vision AI Aerial training data preparation
- AI-enabled drone applications
- Satellite image annotation
- Construction progress tracking by annotation of differences between the images
- Construction site safety
- Equipment tracking
- Property monitoring
- Road traffic reporting
- Pipeline monitoring



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Drones
Drones are widely used in countless scenarios: from military operations to precision
agriculture.
In order to become an effective and useful piece of equipment and go beyond entertainment value,
drones will need a video and image annotation for drone flying training data.
AI-enabled drone applications
- Drones provide real-time aerial views for people and object tracking in hard-to-reach places and and dangerous conditions
- Videos made by drones can also be annotated to identify moving objects and specific events
High Performance
Our annotation techniques produce accurate and fast labeling even for suboptimal raw data. This includes conditions like fog, smoke, rain, vibration and low light. In applications like autonomous disaster intervention the quality of training data is vital to mission effectiveness.
Equipment tracking and property monitoring
Autonomous flying can also be achieved with quantified approach parameters and topographical check-point labels. Quality training datasets can optimize your drone use for:
- Construction site safety
- Equipment tracking
- Property monitoring
- Road traffic reporting



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Field monitoring
Once equipped with proper pattern-matching toolset drones can assist in precision agriculture
- Crop health monitoring
- Ripeness evaluation
- Soil condition assessment
- Pest detection
Satellite images annotation
We are professionals in what we do.
If your project requires image annotation, data collection or any other type of custom dataset,
we will know what to do and how to approach those challenges.
We can create complex geospatial models using satellite photos, GIS and GPS data, annotating
each element with highest precision possible



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