AI-Driven Computer Vision

Automated aerial object detection and classification

Our lightweight CV pipeline delivers real-time identification of drones, aircraft, birds, and aerial anomalies. Optimized for EO/IR sensors, the system produces confidence-scored classifications with annotated bounding boxes.

Core Technologies

Object Detection

Zero-shot models (OWLv2) for rapid dataset curation
YOLO models for real-time operational deployment
Configurable for any target object class
<5.5% false negative rate in automated labeling

Semantic Segmentation

Sky/non-sky separation for enhanced accuracy
Filters irrelevant regions for cleaner detection
Improves performance in complex visual environments

Automated Labeling

Dramatically reduces manual annotation requirements
Strategic frame extraction captures edge cases
Continuous detection-labeling-training improvement cycle

Flexible architecture

API-configurable inference engine
Seamless model swapping and updates
No retraining required for new object classes
Modular design supports future capability expansion

integration

Works with existing optical sensors to modernize C-UAS detection infrastructure. Technology validated through commercial deployment and ready for enterprise adaptation.