Aerial Aircraft Detection and Counting
Airport Operations Provider
Automated aircraft detection and counting from satellite and aerial imagery for airport operations.
Tracking aircraft positions and counts across airport facilities from aerial imagery was a manual process. Analysts spent hours reviewing satellite passes, and counts were often outdated by the time reports were compiled. Dense parking configurations and overlapping aircraft made manual counting error-prone.
Using point detection fine-tuned with reinforcement learning, the Moondream model locates individual aircraft in aerial imagery, even in densely packed airport configurations. The model handles tiled inference for high-resolution satellite images, accurately counting aircraft across large facilities.
- Detection F1 improved from 0.07 to 0.73
- Handles dense airport scenes with 50+ aircraft
- Processes full satellite passes in minutes instead of hours
- Enables daily fleet position tracking across multiple facilities
Complete Vision AI Stack
This solution uses Moondream's integrated stack from model training through production deployment. Every layer is designed to work together, so you go from problem to deployed system without stitching together tools from different vendors.
AI Model Layer
Base Model
Moondream 3
Fine-Tuning
RL via Lens
Production Model
Moondream 3 (fine-tuned)
Deployment Layer
Inference Engine
Photon
Target Hardware
NVIDIA L40
Deployment
Cloud
Training Method
RL
Training Steps
148
Task Type
point
F1
29.5% → 55.1%
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