Eliminating weeds to increase crop yields

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  Weed Detection with Computer Vision

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  Weed Detection with Computer Vision

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  mAP vs AP - Recall vs Precision - Objectness vs Val Objectness - Box vs val Box

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  Recall vs Average of Precision (increasing)

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  F1 Curve (Score)

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  P Curve (confidence vs precision)

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  PR Curve

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  Overall Results comparison

Idea: Eliminating weeds to increase crop yields

Environment Track

Problem:

Weeds are an unwanted intruder in the agricultural business. They steal nutrients, water, land, and other critical resources to grow healthy crops. These intruders can lead to lower yields and inefficient deployment of resources by farmers.

Factors:

One known approach is to use pesticides to remove weeds, but aggressive pesticides create health risks for humans.

Solution:

Computer vision technology can automatically detect the presence of weeds and use targeted remediation techniques to remove them from fields with minimal environmental impact.

Note: The video implementation is not our intellectual property. This is how how our actual product would be.

Built With

• colab
• python
• roboflow
• tensorflow
• vscode
• yolo