Discover the challenges & solutions to 3D LiDAR annotation & 3D data sets for solving autonomous driving or driver assistance

Join the conversation #reworkAI

Speaker:

Original
Duncan Curtis

VP of Product

Samasource

Original
You

200+

Global Participants

What to Expect

    1. Interactive Q&A Get all of your questions answered! You can also pre-submit your questions ahead of time
    2. Hear best practices from Samasource on data quality, data strategy & data annotation
    3. Connect with the AI community during and post-webinar on our Slack channel
    4. Complimentary webinar to allow for accessibility to all
    5. Participate from any device so that if you're on the move or at home, you'll be sure not to miss out!
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WEBINAR: Challenges & Solutions for 3D LiDAR Annotation & 3D Data Sets

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Topics we cover

Enterprise Software

Business Applications

Business Case Studies

Computer Vision

Data Quality

Data Annotation

Data Efficiency

Data Infrastructure

Autonomous Vehicles

Enterprise Software

Business Applications

Business Case Studies

Computer Vision

Data Quality

Data Annotation

Data Efficiency

Data Infrastructure

Autonomous Vehicles

Why Join?

Our webinars explore the latest technology advancements as well as practical examples to apply AI to solve challenges in business and society. We bring together a mix of academia and industry to share their learnings and insights, offering new perspectives for you to take away, as well as the chance for you to ask your burning questions and continue conversations with the community after the webinar, forming new relationships to solve the unthinkable with AI.

  • Speakers

    Webinar Overview

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    Samasource will share the most common issues faced when given the task of solving autonomous driving, including getting the right data, and ensuring it is labeled correctly. Learn more about finding, collecting or creating the right data set to jump-start your ML development. Topics explored will include: matching data set size to your developmental phase; the near-infinite edge cases dilemma; defining the right quality rubric for your 3D LiDAR annotations; and who should label your data?

  • Discover

    Key Takeaways

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    1. Discover how accurate your 3D boxes need to be for LiDAR data
    2. Understand the trade-offs between quality annotations vs volume of data
    3. Learn how to pick the right labeling partner for you
  • Network

    Who Should Attend?

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    • ML Engineer
    • Director of Engineering
    • Lead Engineer
    • Product Owner AI & ML
    • Data Scientist/ Analyst
    • Research Assistant/ Associate
    • Quality Analyst
    • Partner Manager
    • Vendor Support Manager
    • Servant Leader
    • Label Coordinator

Regular Attendees

Ford
volkswagen
Apple
Google
Uber
Toyota
Audi
General Motors
Nissan
renault
Bosch
lyft
Hyundai
huawei
Rolls-Royce Motor Cars
Intel
Microsoft
University of South Carolina
Texas A&M
NVIDIA
Drive Capital
bmw

Summary

The 5th Annual Edition of the San Francisco Deep Learning Summit

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Presentation

Frontiers of Computer Vision: Beyond Accuracy from Sara Hooker, AI Resident, Google Brain

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Interview

Cathy Pearl, Head of Conversation Design Outreach at Google

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Original

Event Organiser/

Nikita Johnson

Founder

Our webinars are all created from scratch and individually curated to share the most up-to-date AI advancements and current global issues for discussion. We look forward to hearing your thoughts, ideas and burning questions!

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Sponsored by

Samasource.001
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WEBINAR: Challenges & Solutions for 3D LiDAR Annotation & 3D Data Sets

Register now
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