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== Problem Areas ==
=== Precision
Can increase the yield, reduce the need for tillage and fertilizers.
* Weed and pest detection
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* Farming assistant
=== Robotic
Development of autonomous robots for performing specific tasks on crops.
=== Monitoring
* Estimating carbon in soil and soil health
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*[https://www.journals.elsevier.com/computers-and-electronics-in-agriculture Computers and Electronics in Agriculture]
*[https://www.springer.com/journal/11119 Precision Agriculture]
=== Workshops ===
* [https://www.cv4gc.org/cv4a2020/ Computer Vision for Agriculture], ICLR 2020
=== Groups and Labs ===
* [https://www.agriculture-vision.com/ Vision for Agriculture]
* [https://www.sydney.edu.au/engineering/our-research/robotics-and-intelligent-systems/australian-centre-for-field-robotics.html Australian Centre for Field Robotics]
== Library and Tools ==
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== Data ==
=== Remote
[[Remote Sensing Datasets]] offers great opportunity to monitor agriculture and can be georeferenced to match ground measurements. In particular, [https://earthengine.google.com/ Google earth engine] offers a convenient interface over freely available satellite imagery such as [https://developers.google.com/earth-engine/datasets/catalog/landsat/ Landsat] and [https://developers.google.com/earth-engine/datasets/catalog/sentinel/ Sentinel].
=== Soil
=== Kaggle
* [https://www.kaggle.com/vbookshelf/v2-plant-seedlings-dataset Plant Seedlings Dataset]
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