Getting the GISt of our food: using AR to fill in the missing link from farm to table
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Updated
Jan 22, 2019 - CSS
Getting the GISt of our food: using AR to fill in the missing link from farm to table
precision agriculture made easy! TechoFarmAustralia integrates drone-based multispectral imaging for in-depth crop monitoring in the NSW Riverina region. Empower your farm with advanced technology, seamless data exchange, and localized insights. Join us in revolutionizing agriculture!
The AvantGarden project and team presentation
AgTech/AgriTech Data Analytics
Public website for the Digital Agriculture Hackathon hosted by Purdue University, University of Kentucky, and Tuskeegee University
In this work we attempt to fill in the gap years for the US Agricultural Census in Utah counties. Open source data from NOAA, Agricultural Census, and BLS are used leveraging Machine Learning methods and models.
A simple simulator that generates latitude/longitude data. Simulates herding cattle north and updates location data every one minute.
Website presentation for the AvantGarden project
Agricultural robots is a repository to explore the use of Github while sharing research about agricultural robotics
A standard model for tracking plant growth, environment, method and entry into the supply chain
Plant disease detection using Machine Learning. This is an open source project that is a continuation from @imskr open source work https://github.com/imskr/Plant_Disease_Detection
Leaf Buster AI is a machine learning project developed during the HackMerced VIII hackathon with the goal of the project being to help farmers identify and classify diseases in their crops using computer vision and artificial intelligence.
Hey, interested in our project. Visit our demo
Farmtech is a tool that aims to help the Tamilnadu farming community optimize crop production. The global demand for food greatly outstrips that for supply, and there is an urgent need for interventions to address this balance.
This is using to collect plant image during growing.
CNN for identifying common diseases on apple leaves.
A dataset for semantic segmentation of Sosnowsky's hogweed in the ground-level view photos taken in St. Petersburg, Malaya Vishera, Pushkin, etc.
The Sencrop JavaScript API client
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