Mr. David Tareen

Global AI product Marketing Director Raleigh-Durham, North Carolina Area.

Lessons learned from 5 real AI deployments around the world

What happens when you deploy 5 very real and diverse AI projects around the world? This talk will cover the stories of five real use cases including Volvo trucks, Swisscom, large European retailer and others. Each use case will go over the customer, their business problem they were trying to solve with AI, the process of how the solution was developed, the outcome and finally, a lesson learned that can be applied to a broad set of AI projects around the world. The technologies covered in this talk will include AI, machine learning, deep learning, computer vision, natural language processing, Internet of Things (IoT) and forecasting. 

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Professor Fresenius University, Germany

AI-Virtual Reality in Refugee Aid / Government Integration

 This overview is intended to present the previous efforts in the field of AI and virtual reality in refugee aid on the one hand, and to give an outlook on the upcoming studies of the working group on the other hand.


AI-VR for the relief of voluntary helpers

With approx. 1.9 million asylum applications since 2010 in the whole of Germany, the federal states have an enormous number of procedures to process and high integration work to perform.

To know more about this visit our Conference AI 2020

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Department of Electronics, Govt. Model Engineering College, Kochi, India.

Deep Learning based automatic detection of Alzheimer’s Disease using Magnetic Resonance Images

Alzheimer’s Disease (AD) is a progressive mental deterioration and incurable neurodegenerative disease that can occur in middle or old age, due to generalized degeneration of the brain. Because of the irreversible nature of the progression of Alzheimer’s Disease, the early diagnosis of AD has an immense clinical, social and economic need. This research output is proposing a state-of-the-art, easy and early automated deep learning based system to predict AD from a large MRI dataset of normal and diseased subjects. It classified the database of 111 subjects into Mild Cognitive Impairment (MCI), Alzheimer’s Disease (AD), and Normal classes.

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