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Cesar Romero

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September 17, 2020

Training a performant object detection ML model on synthetic data using Unity computer vision tools

ByYou-Cyuan Jhang, Adam Palmar, Bowen Li, Saurav Dhakad, Sanjay Kumar Vishwakarma, Jonathan Hogins, Adam Crespi, Chris Kerr, sharmila-chockalingam, Cesar Romero, Alex Thaman, Sujoy Ganguly

Supervised machine learning (ML) has revolutionized artificial intelligence and has led to the creation of numerous innovative products. However, with supervised machine learning, there is always a need for larger and more complex datasets, and collecting these datasets is costly...

in Engine & platform | 10 min. read

June 10, 2020

Use Unity’s computer vision tools to generate and analyze synthetic data at scale to train your ML models

ByAdam Crespi, Cesar Romero, Srinivas Annambhotla, Jonathan Hogins, Alex Thaman

Synthetic data alleviates the challenge of acquiring labeled data needed to train machine learning models. In this post, the second in our blog series on synthetic data, we will introduce tools from Unity to generate and analyze synthetic datasets with an illustrative example of ...

in Engine & platform | 7 min. read

May 1, 2020

Synthetic data: Simulating myriad possibilities to train robust machine learning models

BySrinivas Annambhotla, Cesar Romero, Alex Thaman

Synthetic data helps many organizations overcome the challenge of acquiring labeled data needed for training machine learning models. This blog kicks off our series on synthetic data for training computer vision systems. In this first post, we will provide a brief overview of syn...

in Technology | 4 min. read

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