Daniel — ML and Data Science Developer
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This was a project for a carsharing hiring. The project involved creating a system that allowed it to detect and recognize all the faces in the car as well as to detect whether any persons are smoking. The system was required to work offline which was an added challenge. Daniel created a facial recognition solution that could then be embedded into the car’s computer device. He also implemented a cigarette detection solution and a microservice for preparing face vectors to allow for comparison on a device.
Read moreA solution was needed for merchandisers who compare the real arrangement of goods (realograms) with a plan (planogram). OCR and one-shot learning were used to search the product database using triplet loss network training. The generation of images in Blender was required, as was the development of tools marking real goods. Daniel experimented with various detection and classification approaches, taught OCR models, developed image generation using Blender, and ported and optimized models for Android devices.
Read moreA project that was required to find athletic starting signals or shots on a soundtrack. Daniel helped develop an architecture using convolutional and recurrent neural networks. He was also required to allow the system to be able to separate shots coming from other directions, which are not important.
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