David Okosa
Computer Vision & Edge Deployment for Mechanical Systems
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Detects unwanted human presence in predefined areas, can be deployed on device or over a server with RTSP streaming enabled. Configurable intruder email and SMS alert systems. Different model configurations with varying accuracy and detection FPS.
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Optimized machine learning model, works in extremely resource constrained environments while retaining good accuracy and recall. Detects 7 emotions.
Utilizes NCNN (a high perfomance neural network framework), to achieve 79% accuracy @ 90fps.
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Multi-modal machine learning service, back-end integration with fastapi. Automatically redacts sensitive PII (Personal Identifiable Information) from documents, performs bulk operations. Link to project on github: https://github.com/fw7th/redact
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