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

Speech recognition model for transcribing spoken language into text .

Deep learning system to upscale and enhance low-resolution images while preserving fine details.

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 lightweight face recognition solution leveraging Edge Impulse’s FOMO model, designed for fast, accurate deployment on edge devices in industrial environments.

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

Robust speaker ID/verification using ECAPA-TDNN embeddings for secure, personalized HMI and analytics.

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

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