Autonomous Vehicle Data Annotation

Autonomous Vehicle Safety & Security

Вміст надано Hasan Akram. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Hasan Akram або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.

3y ago 47:53

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Annotating the data in the correct way is very important for the autonomous vehicle industry. It is the process of tagging or classifying the objects in the frame as captured by the autonomous vehicle.

In this episode, Philip Kessler will talk about Understand.ai and how their company annotates data. Among other interesting topics, he will also answer questions such as:

What are the problems being addressed by Understand.ai?

How big is the annotation industry today?

How often do we have to do data annotation?

When it comes to AI, why do we need global data?

How does Understand.ai annotate complex data?

What are the different types of annotation?

What is Understand.ai’s primary business model?

How does Understand.ai validate the correctness of their annotation?

How is data security handled?

What are the main business and technological challenges of Understand.ai?

By the end of this insightful discussion, you will have an idea of how data annotation works in autonomous driving and how Understand.ai performs this task.

#artificialintelligence #machinelearning #dataannotation #annotations #AutomotiveIndustry #autonomousvehicles #autonomousvehicle #Ai #artificialintelligenceai #artificialintelliegence

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#Auto #Lifestyle #Hasan Akram #Autonomous Vehicles