Onboard artificial vision capabilities in public transportation are critical to ensuring the safety and well-being of passengers and personnel as well as for maximizing the overall customer experience. Now, AI-enabled Deep Learning is bringing new possibilities to the attention of rail, tram and bus operators. How can embedded developers cost-effectively maximize the potential of AI for their onboard applications and what are the key considerations when accelerating neural networks?
Whitepaper topics discussed by Kontron and Intel:
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The design considerations and challenges facing embedded systems designers when developing AI-enabled vision applications for deployment onboard trains and other public transportation vehicles. |
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The critical role of neural network acceleration for delivering the full potential of Deep Learning for systems performance and functionality. |
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Kontron’s family of Intel-based EN50155 TRACe BoxPCs with neural network acceleration and its micro-cloud platform with Genetec™ Security Center. |