Fast object detection using YOLOX optimized for embedded edge devices.

Efficient CNN model for image classification on mobile and embedded edge devices.

Lightweight anomaly detector for time series data using Isolation Forest, designed for edge environments.

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

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-accuracy speech transcription optimized for automated documentation and voice-controlled operations in demanding environments.