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Computer Vision in Agriculture

Process insights for your AgriTech (Agricultural Technology) solutions from variety of data sources. Activeloop supports it all - from satellite, aerial, & drone images from the sky to the sensory data on the ground

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Livestock counting

Detect all of your livestock across various locations by deploying animal detection models

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Plant and weed identification

Reduce the dependence on herbicides by automatically differentiating weeds from plants

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Harvesting, grading and sorting

Deploy solutions to streamline the sorting of harvested crops according to features such as ripeness, size, and imperfections

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Field & soil health monitoring

Detect drought-stress or overwater occurrences or nutrient deficiency to deliver fertile soil & plants

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Plant disease & pest detection

Identify areas that are experiencing pest or disease pressure to apply fungicides pesticides and protect yields

Agricultural Datasets for Machine Learning

Don't have proprietary data? Get a head start by using one of the public machine learning datasets for agriculture available through Activeloop for weed identification, object detection, livestock counting, and more

  • lincolnbeet dataset visualization on Activeloop Platform
  • Explore agricultural datasets
    to detect sugar beets or weeds ...
  • satellite dataset visualization on Activeloop Platform
  • ... identify drought or overwatering ...
  • animal-pose dataset visualization on Activeloop Platform
  • ... or count your livestock!

AgriTech is transforming agriculture. Make it legen-dairy with ML powered by Activeloop

Robotics, as well as data from sensors, airplanes, & satellites, powered by computer vision, supercharges agriculture.

Farmers can nowmake smarter, faster decisions that improve crop yields, optimize usage of nutrients and water, and keep the pests away. A variety of tasks that took anything between hours to weeks can now take just minutes - from field & soil health monitoring, to catching diseases and pests before they become a major problem. On the ground tasks, such as livestock counting, harvesting, grading and sorting, as well as edge tasks such as weed identification can now take mere seconds.

With AgriTech solutions, farmers can understand what is happeing before it is visible to human eye, and without deploying workers to the fieldsWith Activeloop, machine learning teams working on AgriTech solutions are able to quickly slice up the high-resolution images into smaller images (with our tiling feature), stitch them together however they see fit, visualize and query their data and stream to their machine learning models while training them at scale.

Machine Learning Case Study: AgriTech

Harvest season constrains the timeframe in which you can retrain your models on the new data to extract valuable insights on-the-fly. With our scalable ML data infrastructure, we helped IntelinAir achieve just that

Better AgriTech solutions with scalable aerial data pipelines

Learn how IntelinAir, a leading AgriTech company, transformed 1.5 petabytes of aerial data into vital insights for farmers with scalable plug-and-play data pipelines

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Machine Learning Case Study: ClimateTech, Reforestation

Earthshot Labs branched out to measure tree data with precision, turning reforestation projects into a walk in the park. Learn how we streamlined the team’s collaboration and pruned those pesky data quality issues for a flourishing future

Faster Tree Segmentation for Earthshot Labs

Discover how Earthshot Labs disrupted forest inventory with a mobile app, making data collection 5x faster & with 4x fewer resources. With Deep Lake’s version control & visualization they improved data quality, & enhanced collaboration with data streaming, resulting in increased model accuracy.

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