Tony — ML and Data Science Developer
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For the Dozor Project with a car-sharing company, Tony developed an Android app featuring facial recognition to verify authorized drivers and a novel smoking detection capability, designed from scratch. This required extensive research, data collection, and experimentation with neural networks, resulting in an accurate, offline-capable system for embedded car systems.
Read moreIn the BusFactor project, Tony focused on monitoring public transport drivers for mobile phone use while driving, ensuring correct camera alignment and continuous operation within the driver's cabin. He successfully managed the deployment of these models onto the client's systems.
Read moreFor a merchandising solution, Tony worked on recognizing goods on shelves, comparing actual product arrangements with planned layouts. This involved OCR, one-shot learning, image generation in Blender, and the development of marking tools for real products. He explored various detection and classification methods, optimized models for Android devices, and experimented with OCR and one-shot learning techniques.
Read moreIn the Hitfactor project, he contributed to developing a system to detect athletic starting signals or shots in soundtracks using convolutional and recurrent neural networks. Tony improved the system's accuracy in identifying relevant sounds by employing clustering algorithms, distinguishing important shots from background noise.
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