Efficient single-camera depth estimation using quantized MiDaS v2 model optimized for edge AI deployment.

Real-time environmental sound classifier optimized for low-power edge devices using MobileNet v1.

Real-time activity recognition using motion sensor data from wearable fitness devices.

Speech recognition model for transcribing spoken language into text .

AI-based detection for product recognition and user interaction in smart vending systems.

Facial emotion analysis for adaptive, personalized HMI experiences.

Efficient edge analytics using Qualcomm HW to extract facial attributes for personalization and safety.

Industrial image segmentation and background removal for visual inspection and automation.

Acoustic event detection for machinery monitoring and anomaly prevention in noisy industrial settings.

Flexible model training and validation experience with deployment and inference on SECO edge hardware.