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AI solutions tailored for the defence industry

 

Reduce AI innovation risks and exceed product development goals.

  • Intelligence, surveillance and reconnaissance - target acquisition and battlefield simulations optimised with deep learning
  • Autonomous systems - computer vision-based automatic mission support services
  • Chemical analysis - ML trained models for contaminant detection and spectroscopic analysis
  • Fault prediction & prevention - cutting edge modelling at both device and system level

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Project descriptions

Military grade DPV detector
Military grade DPV detector 2
Military grade DPV detector 1

Military-grade DPV detectors

 

Working with petabytes of data, we created a comprehensive training pipeline capable of detecting and differentiating drones, people and vehicles.

Target tracking and re-identification

 

Combining information from multiple sources (thermal cameras, visual light cameras, motion detectors) we helped our client deploy a fully integrated surveillance system.

Target tracking and re identification
Target tracking and re identification 2
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Automatic payload monitoring system
Automatic payload monitoring system 1
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Automatic payload monitoring system

 
We developed a GPU-accelerated method which automatically detects which equipment payloads (fuel, ammunition, etc) are being loaded onto an UGV to support military.personnel.

Follow me system for UGVs

 
To ease the transportation of heavy equipment we developed a UGV-based solution which can intelligently track and follow human personnel and/or vehicles using both camera and LiDAR sensor data.
Follow me system for UGVs
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Unified battlefield system
Unified battlefield system 2
Unified battlefield system 1

Unified battlefield system

 
By integrating multiple sources (visual light & thermal camera, radar, motion detectors, target tracker and classifiers) we created an easy to use, holistic surveillance and battlefield observation system. Self improving surveillance system

Self-improving surveillance system

 
Using both temporal and spatial consistency analysis we created an ML module which analyses its own decisions in real-time for re-training and self-improvement.
Self improving surveillance system
Self improving surveillance system 1
Self improving surveillance system 2
Chemical analysis
Chemical analysis 1
Chemical analysis 2

Chemical analysis

 
An ML segmentation model was trained to detect reacted surfaces on military transport vehicles, thereby detecting chemical contamination which was then displayed via a military grade VR helmet

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“AI solutions tailored for the defence industry”