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Date: September 2, 2020
Time: 9:00 AM PDT | 6:00 PM CET
Duration: 1 hour
Time: 9:00 AM PDT | 6:00 PM CET
Duration: 1 hour
NVIDIA and system integrator Tata Consultancy Services (TCS) experts will share the key pillars of autonomous driving development and infrastructure, focusing on object detection inference pipeline for deploying self-driving systems at scale.
Comprehensively training the robust deep neural networks that make up an autonomous vehicle’s perception system requires massive amounts of labeled data. We’ll share insights on optimization techniques and full stack architectural components to maximize pre-trained model inference performance.
This webinar will cover the data annotation pipeline in the autonomous vehicle training addressing the sensitivity to variations in data distribution, data type, annotation requirements, quality parameters, the volume of data, and the effectiveness of automation critical to achieving optimal annotation accuracy and speed.
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DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
DGX Station Whitepaper
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
Dive deeper into the DGX Station and learn more about the architecture, NVLink, frameworks, tools and more.
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Speakers
Manish Harsh
Global Developer Relations - Autonomous Driving, NVIDIAManish Harsh is a global developer relations manager for autonomous vehicles at NVIDIA, working with OEMs, startups and partners developing self-driving technology. With 15+ years of experience, Manish is focused on sharing best practices for AV infrastructure, enabling end-to-end AI development, training, testing and validation at scale. He holds a bachelor’s degree in electronics engineering from Pune University, India and is pursuing a management degree from University of California, Berkeley on leadership and technology management.
Pallab Maji
Sr. Solutions Architect – Deep Learning, NVIDIAPallab Maji is a machine learning senior solutions architect at NVIDIA working with system integrators globally. His research interest lies in design and development of perception systems for autonomous vehicles, focusing mostly on computer vision and machine learning. Pallab holds a doctoral degree in artificial intelligence and a master’s degree in signal processing from National Institute of Technology, Rourkela, India.
Patricia de Boer (Host)
Global Automotive Partner Executive, NVIDIAPatricia manages global system integrator partners focusing on autonomous vehicle AI infrastructure and AI applications for development and testing, helping transform the business and operating models of automakers and Tier1 suppliers. She has helped build new markets, products, and transform companies for more than 20 years in AI and data science, autonomous vehicles, IoT, cloud, and automation.
Sanjay Dulepet
Global Head - Product Development, Connected and Autonomous Vehicle Strategic Initiative, TCS
Sanjay Dulepet is the global head of product development and a technology leader at TCS, focusing on autonomous and connected vehicle strategic initiatives. Sanjay is in charge of driving innovation with an entrepreneurial product mindset through strategic partnerships with industry leaders, startups, and academia. He holds a master's and bachelors's degree in computer science.
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