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.

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

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

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.

High-accuracy speech transcription using Wave2Vec for industrial documentation, healthcare automation, and voice-controlled processes.

Energy-efficient object detection optimized for edge platforms with power and thermal constraints.