Understanding NDVI & NDRE Indexes in Crop Disease Prediction
We break down how near-infrared (NIR) and red-edge spectral bands identify chlorophyll density changes before physical lesions form on wheat crop leaves.
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Training U-Net Models for Leaf Rust Early Segmentations
Inside our leaf-level neural networks. How IPS CeresAI isolates fungal spores from dry dirt shadows, achieving a 94% classification precision target.
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Time-Series Regression Curves in Harvest Schedule Planning
How daily cumulative solar radiation values and moisture sensor records help wheat cooperatives estimate yield weight targets with under 6% error.
Read Article (5 min)Dynamic Orthomosaic Stitching Over 100 Hectare Fields
Processing thousands of drone raw images is resource-intensive. Learn how our cloud run pipeline automates coordinate alignment and stitching maps.
Read Article (7 min)The Self-Funded Advantage: IPS CeresAI's First Six Months
Operating lean allowed us to focus entirely on building high-fidelity model pipelines alongside regional cooperatives. Here are the key technical takeaways.
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