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Date: February 18, 2021
Time: 9:00am – 10:00am PT
Duration: 1 hour

Image segmentation deals with placing each pixel of an image into specific classes that share common characteristics. It’s widely used in many fields, including manufacturing, autonomous driving, medical imaging, and more.

However, building, training, and optimizing an image segmentation model can be quite time consuming for novices and experts alike. To achieve a state-of-the-art model, you need to set up the right environment, train with the correct hyperparameters, and optimize it to achieve the desired accuracy. In this webinar, you’ll explore the NVIDIA® NGC™ catalog—which has a whole host of GPU-optimized AI software such as containers, pre-trained models, and use case-based Jupyter notebooks—and how to use these resources to kickstart your AI journey.

In this webinar you will learn:
  • About the NGC catalog and how it helps accelerate your AI workflows
  • How to leverage a Jupyter notebook containing a pre-trained image segmentation model that can be used to detect defective parts in an industrial application
  • How to refine the model by retraining it using your own hyperparameters and test it using your own checkpoints
Join us after the presentation for a live Q&A session.

Click here to register for the next session on Recommender Systems at 11am PT



You will receive an email with instructions on how to join the webinar shortly.

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Akhil Docca

Senior Product Marketing Manager, NGC, NVIDIA

Akhil Docca is a senior product marketing manager for NGC at NVIDIA, focusing in HPC and DL containers. Akhil has a Master’s in Business Administration from UCLA Anderson School of Business and a Bachelor’s degree in Mechanical Engineering from San Jose State University.

Shokoufeh Monjezi Kouchak

Technical Marketing Engineer, NVIDIA

Shokoufeh is a technical marketing engineer at NVIDIA, focusing on deep learning models. Shokoufeh obtained her Phd degree in computer engineering from Arizona State University, where she focused on driver behavior analysis and driver distraction detection with deep learning models.

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Webinar: Description here

Date & Time: Wednesday, April 22, 2018