BEGIN:VCALENDAR PRODID:-//Microsoft Corporation//Outlook 16.0 MIMEDIR//EN VERSION:2.0 METHOD:PUBLISH X-MS-OLK-FORCEINSPECTOROPEN:TRUE BEGIN:VEVENT CLASS:PUBLIC CREATED:20180511T151823Z DESCRIPTION:Deep Driving Technologies & Computer Vision for Cognitive Vehic les | September 23 - 25\, 2018 | Maritim proArte Hotel Berlin \n \nAuto.AI Europe Key Topics\n \nDEEP DRIVING\, MACHINE LEARNIN G & COMPUTER VISION\n* Algorithms and data schemes\n* De ep neural networks / deep learning and neural networks: Challenges for de cision making algorithms in heavy traffic\, self-driving vehicles\n* Data processing and AI: Software architecture and hardware challenges\ n* Path planning and object recognition with AI / future pathways \, required research and the role of deep learning in the mix of computer vision approaches\n* Tools for enabling deep learning systems\n* Full stack software suites for AI in ADAS providing hardware agno stic\, scalable solutions\n* Deep learning for human-centered sem i-Autonomous Driving\n* Role of cognitive computing systems and d eeper direct perception in Autonomous Driving/ in Level 4 and 5 cars\n* Artificial reality? Deep learning with synthetic data from driving simulations\nSENSOR FUSION\, DATA & AI\, IMAGING & PERCEPTION\n* Algorithms for cameras as primary sensors for accomplishing the tasks of o bject recognition and classification\, localisation\, decision making\, tr ajectory planning and vehicle control\n* Visual processing to ADA S: applications\, architectures and algorithms\n* Deep learning w ith multi-sensor data and self-healing map for Automated Driving\n* Imaging vision in automotive linked cameras/ISP: processing chain\, alg orithms and camera systems architecture\n* How neural nets can le verage domain-specific knowledge in computer vision\n* Automotive camera technology and computer vision algorithms\n* Collaborativ e sensor fusion to improve sensing of the fused system\n* Neural networks in sensors\n* Multi-core processing approaches for AI dr iven autonomous vehicles\n* Software architectures for AI and dee p driving\n* Sensor fusion deep learning architectures\nSpeaker P anel: http://auto-ai.eu/speakers\n \nWhat can you expect @ Auto.AI Europe? http://auto-ai.eu/who-why\n \nHow to attend? Tickets: http://auto-ai.eu/b ook-now\n DTEND;VALUE=DATE:20180926 DTSTAMP:20171221T154825Z DTSTART;VALUE=DATE:20180923 LAST-MODIFIED:20180511T151823Z LOCATION:Maritim proArte Hotel Berlin PRIORITY:5 SEQUENCE:0 SUMMARY;LANGUAGE=de:Auto.AI Europe TRANSP:TRANSPARENT UID:040000008200E00074C5B7101A82E00800000000C010BC847B7AD301000000000000000 0100000007BCC237F6B730241A6F08406ED465216 X-ALT-DESC;FMTTYPE=text/html:< !--[if gte mso 10]>

Deep D riving Technologies &\; Computer Vision for Cognitive Vehicles | September 23 - 25\, 2018 | Maritim proArte Hotel Berlin

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Auto.AI Europe Key Topics

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DEEP DRIVING\, MACHINE LEARNING &\; COMPUTE R VISION

*          Algorithms and data schemes

*          Deep neural networks  / deep learning and neural networks: Challenges for decision making algorithms in heavy traffic\, self-driving vehicles

*          Data processing and AI: Software architecture and hardware challenges

*           Path planning and object recognition with AI / future pathways\, required research and the role of deep learning in the mix of computer vision approaches

*          Too ls for enabling deep learning systems

*          Full stack software suites for AI in ADAS providing hardware agnostic\, scalable solutions

*          Deep learning for human-centered semi-Autonomous Driving

*           Role of cognitive computing systems and deeper direct perception in Autonomous Driving / in Level 4 and 5 cars

*          Artificial reality? Deep learning with synthetic data from driving simulat ions

SENSOR FUSION\, DATA &\; AI\, IMAGING &\; PERCEPTION

*           Algorithms fo r cameras as primary sensors for accomplishing the tasks of object recognition and classification\, locali sation\, decision maki ng\, trajectory planni ng and vehicle control

*          Visual processing to ADAS: applications\, < span class=SpellE>architectures and algorithms

*           Deep learning with multi-sensor data and self-healing map for Automated Driving

*          Imaging vision in automotive linked cameras/ISP: processing chain\, algorithms and camera systems < span class=SpellE>architecture

*          How neural nets can leverage domain -specific knowledge in computer vision< /o:p>

*           Automotive camera technology and computer vision algorithms

*          Collaborative sensor fusion< /span> to improve sensing of the fused system

*           Neural networks in sensors

*          Multi-core processing appro aches for AI driven autonomous vehicles

*           Software architectures for AI and deep driving

*          Sensor fusi on deep learning architectures

Speaker Panel: http://auto-ai.eu/speakers

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What can you expect @ Auto.AI Europe? http://auto-ai.eu/who-why

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How to attend? Ticket s: http://auto-ai.eu/book-now

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