Use cases
Quality assurance
Deep Learning for image classification
Classification of objects in different degrees of deterioration or maturity to discard in real time while on the production line or massively.
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Maintenance
Anomaly detection and predictive maintenance
Anomaly location to focus maintenance effort on areas of greatest need and help plan your team's work orders.
Inspections
Object detection and classification
Troubleshooting to focus the maintenance effort on the areas of greatest need and help plan your team's work orders.
Damege assessment
Damage detection and classification
Damage location and damage level classification, identification of damaged parts for automating the repair cost.
Capabilities
Detection
Object detection ranging from protective gear on people to identifying facilities from satellite imagery.
Classification
Enables decision-making regarding product quality or characteristics, allowing sorting and filtering in automation processes.
People
Headcount, demographic statistics by age or gender, occupancy management, and safety measures.
Anomalies
Real-time anomaly detection and event/alert classification. Supports monitoring of industrial and retail environments, even across large areas.
Inspections
Automated processing of thousands of images per hour to locate, tag, and classify items within inspection samples.
Thermography
The system integrates standard, thermal, or X-ray sensors and cameras to capture environmental data. These can be mobile, deployed via drones or robots.