Stanford CS230 grad students research the next generation of AI-driven land urban air vehicles
Andrew and Seraj are masters graduate researchers at Stanford University attending CS230 Deep Learning. Their research project focused on identifying suitable areas to land urban air vehicles through satellite imagery.
Using model-assisted labeling to speed up annotation efficiency with Labelbox
Recently, a team of researchers at the Institute of Industrial Science, a part of The University of Tokyo, leveraged Labelbox's model-assisted labeling features in order to speed up their machine learning processes by 2-3x.
Live webcast (4/24)- How to build world-class AI applications with Labelbox
We're excited to invite you to our upcoming product webinar: How to build world-class AI Applications with Labelbox. The virtual event will be held next Friday, April 24 at 10am PST, we'll also send a recorded version to registrants. During the live webcast, we'll be covering: Some best practices for
Introducing the Labelbox NLP labeling editor: sign up for early access
We’re excited to announce the closed beta of our Natural Language Processing (NLP) product: a brand new Named Entity recognition (NER) and text classification labeling system. Labelbox customers are among the largest enterprises that are rapidly growing their machine learning practices and want a unified platform to create and