Neural network model for forecasting household electricity consumption using historical time series data.

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

Lightweight semantic segmentation model optimized for real-time street scene analysis on edge devices.

Lightweight and quantized PoseNet model for real-time multi-person pose estimation on edge hardware.

Lightweight real-time people counting model based on quantized YOLOX, optimized for edge devices using LiteRT (TensorFlow Lite) .

Real-time AI-powered vision system for detecting defects in manufacturing environments

Secure face recognition HMI system for personalized user access in industrial environments.

High-resolution neural network for accurate keypoint detection in human pose estimation tasks.

HMI system that uses AI to recognize operators during alerts and show personalized troubleshooting instructions.

Detects critical alarm sounds (e.g., fire alarms) and triggers immediate machine shutdown for safety compliance.

AI-powered image analysis tool for defect detection in industrial environments, with a guided journey for customizing new defect types.

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