Powering computer vision in Precision Agriculture
Weaving human and machine intelligence to help deep learning teams reach production at scale
Enriching AI capabilities in
Computer vision models can improve a wide range of farming applications – from monitoring crops and produce to livestock and aquaculture. Developing such applications, however, means working with unstructured, unpredictable, and highly dynamic environments, in which terrain and targeted objects vary and change constantly. Preparing agricultural data also requires expertise, both during analysis and implementation.
To answer such demands, Dataloop’s platform integrates automatic active learning and data processing functions, combined with expert human-in-the-loop workforce for data validation. This means you can use your models to pre-annotate and pre-process data that comes directly from your production environment, then have expert annotators audit and fix only edge cases – resulting in continuously improved model accuracy and significant saving of resources and time, even in highly dynamic and diverse agricultural settings.
Dataloop's real-world applications in agtech
Select use cases that Dataloop advances
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Enterprise-grade data engine
Ensuring highest data standards that serve your entire data organization, allowing cross-functional collaboration while keeping your data access internal
“We love working with Dataloop; their data management platform allows us to simultaneously ensure multiple projects are labeled, tasked and QA'd regardless of where our workforce is based.”
“The team at Dataloop provide a powerful platform with a suite of tools. Thanks to Dataloop, we're able to successfully test our algorithms and improve our ADAS and autonomous driving features"
“Data accuracy is critical to the development of our autonomous systems. Dataloop provides our team with a powerful and intuitive platform that allows us to create top quality and accurate datasets”