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California Crop Yield Benchmark: Combining Satellite Image, Climate, Evapotranspiration, and Soil Data Layers for County-Level Yield Forecasting of Over 70 Crops
Hamid Kamangir, Mona Hajiesmaeeli, Mason Earles
California is a global leader in agricultural production, contributing 12.5% of the United States total output and ranking as the fifth-largest food and cotton supplier in the worl…
AgRowStitch: A High-fidelity Image Stitching Pipeline for Ground-based Agricultural Images
Isaac Kazuo Uyehara, Heesup Yun, Earl Ranario +1
Agricultural imaging often requires individual images to be stitched together into a final mosaic for analysis. However, agricultural images can be particularly challenging to stit…
iNatAg: Multi-Class Classification Models Enabled by a Large-Scale Benchmark Dataset with 4.7M Images of 2,959 Crop and Weed Species
Naitik Jain, Amogh Joshi, Mason Earles
Accurate identification of crop and weed species is critical for precision agriculture and sustainable farming. However, it remains a challenging task due to a variety of factors -…
Enlisting 3D Crop Models and GANs for More Data Efficient and Generalizable Fruit Detection
Zhenghao Fei, Alex Olenskyj, Brian N. Bailey +1
Training real-world neural network models to achieve high performance and generalizability typically requires a substantial amount of labeled data, spanning a broad range of variat…