HYPRFOCAL LABS
Advanced AI Technology
Pushing the boundaries of passive autonomous detection with purpose-built neural architectures, dual-camera fusion, and edge-optimized inference pipelines.
AI/ML Detection Pipeline
From raw camera input to actionable intelligence in under 100 milliseconds.
Raw Camera Data
Ingest streams from wide FOV and narrow FOV PTZ cameras.
Preprocessing
Noise reduction, calibration, and temporal alignment.
Feature Extraction
Isolate salient signatures via spectral and spatial analysis.
Neural Network
Multi-stage deep learning inference on fused feature maps.
Classification
Object ID with confidence scores and threat categorization.
Decision Engine
Rules-of-engagement evaluation and response orchestration.
Dual-Camera Fusion
Correlating wide FOV detection with narrow FOV PTZ tracking for a unified threat picture.
OEAGLE combines wide field-of-view cameras for broad-area detection with narrow FOV PTZ cameras for precision tracking and classification. By correlating detections across both camera systems in real time, the platform achieves confidence levels unattainable by any single camera alone — all through fully passive, emit-nothing operation.
Wide Field-of-View Cameras
High-resolution wide-angle cameras provide persistent broad-area surveillance, continuously scanning the sky for aerial threats. AI-driven detection algorithms process the full panoramic feed in real time to identify and flag potential UAS targets.
Narrow FOV PTZ Cameras
Once a target is detected by the wide FOV system, narrow field-of-view pan-tilt-zoom cameras automatically slew to the target for high-magnification visual confirmation, precise classification, and continuous tracking.
Detection & Classification
Deep neural network architectures purpose-built for airspace threat identification.
Our classification stack chains a custom backbone feature extractor with multi-head attention modules and a lightweight detection head optimized for real-time throughput. The architecture supports dynamic input resolutions and adapts inference precision (FP32 / FP16 / INT8) to match available compute resources.
Real-Time Inference
Optimized TensorRT and ONNX runtime pipelines deliver sub-100ms end-to-end latency from camera frame to classified output, even on resource-constrained edge hardware.
Transfer Learning
Pre-trained on millions of annotated airspace images, our models fine-tune rapidly to new operational environments, threat profiles, and camera configurations with minimal labeled data.
Edge Deployment
Purpose-built for tactical edge environments. Models run on NVIDIA Jetson, Qualcomm SNPE, and custom FPGA accelerators with no cloud dependency for air-gapped installations.
Continuous Learning
Deployed systems feed anonymized detection events back to the training pipeline, enabling model updates that adapt to evolving UAS threats and evasion tactics over time.
Performance Metrics
Validated across thousands of hours of live operational data.
Performance benchmarks measured under operationally representative conditions including cluttered urban environments and adverse weather. Results independently verified against DT&E and OT&E test protocols.
Experience Our Technology
Schedule a technical deep-dive with our engineering team and explore how OEAGLE's AI pipeline can integrate with your defense architecture.