The ramp project is working with the World Health Organization to map healthcare buildings, a tool that will support humanitarian emergency response teams in the likelihood of the next pandemic. In this blog post, we discuss the labeling process, answering a fundamental question: How can we ensure generating high-quality labels working with remote teams?
“What is good enough” is a living question that has evolved over the span of the ramp project. It starts at the end, in defining our use case and engaging end-users as advisors to get an idea of how the model outputs will be utilized. Working backward in this way has allowed us to craft our approach to establishing training data guidance and quality assurance . . .
The ramp project is an ambitious endeavor for many reasons, not the least of which is the curation and open release of high-quality training data in the form of tens of thousands of high-resolution imagery chips with accompanying labels that “teach” our machine learning model . . .
Diversity, Equity, Inclusion – living our values as a small business Diversity, Equity, and Inclusion are priorities for DevGlobal. As the world navigates a new