Real-time face detection for industrial HMI applications.

Classifies physical activities in real time from wearable motion sensor data.

Detects face presentation attacks and verifies liveness from RGB images to strengthen biometric authentication systems..

A training pipeline for customizing YAMNet to recognize new environmental or industrial sounds.

Recognizes hand gestures over time to enable touchless human–machine interaction on edge devices.

Predicts ground settlement around tunnel boring operations using geotechnical and TBM operational data.

Segments foreground objects from image backgrounds to support automated industrial vision and inspection workflows.

Detects and maps land-cover changes from multi-temporal satellite or aerial imagery for environmental monitoring and urban analysis.

AI vision application to detect human falls in real time for safety, elderly care, and industrial risk monitoring.

Classifies human actions from video sequences to support activity understanding, workflow analysis, and safety applications.

Guided training environment for creating and preparing custom Face Recognition models, with optimized deployment and inference on SECO hardware.

Energy-efficient object detection optimized for edge platforms with power and thermal constraints.