Agriculture

We simulate multiple placement scenarios, various environmental conditions, plant growth stages and annotation schemes to create large sets of diverse datasets.

How Synthetic Data Can Help

Successful agricultural operations rely on a massive and ever changing barrage of variables, from weather, to invasive weeds and species, to pests.

AI and computer vision can help predict and intervene before costly situations cut into revenue and crop quality. We’re working with our partners in the industry to use synthetic environments and subsequent data and annotations to create the smartest fields.

Use Cases

Agriculture Weed Detection

WEEDS DETECTION

Reduce the use of pesticides by identifying noxious weeds.

Agriculture Plant Growth

PLANT GROWTH

Monitor the different stages of plant growth and optimize production.

Agriculture Crop Sorting

CROP SORTING

Optimize the methods of sorting crops to reduce food waste.

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AI.Reverie’s agricultural environments with dynamic scenario generation and automated annotations (2D bounding boxes and segmentation masks).

OUR INDUSTRIES