AgriTech: Smarter Farming with Machine Learning
Apply computer vision in agriculture to improve crop quality & yields, livestock health, and increase your profits.
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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
Livestock counting
Detect all of your livestock across various locations by deploying animal detection models
Plant and weed identification
Reduce the dependence on herbicides by automatically differentiating weeds from plants
Harvesting, grading and sorting
Deploy solutions to streamline the sorting of harvested crops according to features such as ripeness, size, and imperfections
Field & soil health monitoring
Detect drought-stress or overwater occurrences or nutrient deficiency to deliver fertile soil & plants
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
- Explore agricultural datasets
to detect sugar beets or weeds ...
- ... identify drought or overwatering ...
- ... 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
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.
