Agriculture
Spot early signs of disease for yield maximization and pest prevention using AI
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Agriculture
Computer Vision in the Agriculture industry has made leaps and bounds but tend to be confined to processing plants. Datature takes it to the field by enabling growers to spot early signs of disease for yield maximization and pest prevention as well as automate manual tasks like weeding and picking.
Crop Disease Detection
Utilising machine learning algorithms to detect diseases in crops based on images on a colossal scale and prevent losses within crop yields.
Crop Grading
Using image processing techniques to provide fruit grading solutions, tackling the laborious nature and inconsistency in inspection and classification process.
Lifestock Monitoring
Machine learning models are able to detect sick animals and predict cattle health & provide early and timely medical care.
Land Management
Using machine learning to optimize land for maximal crop and cattle yield by efficiently utilizing land resources.
Harvest Optimization
Implemented computer vision systems can monitor the growth patterns of crops, and the effect of fertilizers and pesticides & be analyzed to determine ripeness of crops.
Pest Detection & Prevention
Monitoring pests can be labor-intensive and time consuming for agricultural experts. Through computer vision methods, automatic monitoring of different categories of pests will be made possible.
Use-cases in
Agriculture
to inspire your next build
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"The Datature platform provided us a great user experience allowing us to increase our annotation speed by 10x which results in quicker delivery of the model in the market"
Pranav Asthana
Co-Founder & Head of Engineering, Upjao
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