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

Deep learning model to detect presentation attacks in biometric systems, enhancing security against spoofing attempts.

Speech recognition model for transcribing spoken language into text .

A time-series forecasting model designed to predict sensor data patterns in smart buildings, enabling proactive energy management and maintenance.

High-precision OCR application that detects and transcribes text from real-world images with superior accuracy, ideal for industrial and logistics use cases.

Lightweight OCR application that detects and reads text in images using a faster, lower-resource model designed for embedded and edge devices.

Specialized AI-based vision system for detecting surface and structural defects on printed circuit boards (PCBs) during manufacturing inspection.

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

Advanced transformer-based detector optimized for accurate, real-time edge performance on SECO platforms.

Deep-learning gesture recognition for touchless HMI in dynamic environments.

On-device fine-tuning/validation of ResNet classifiers—customize without cloud dependency.

Predictive modeling for TBM settlement to enhance safety and planning in tunneling projects.