paper
2017
Applications & impacts
New model or method
CNN / U-NetRNN / LSTM / ConvLSTMGAN or VAEClassical ML (trees, GP, linear, kernels)Stanford University Journal
2017-02-12
034
Feb 2017
Jiaxuan You, Xiaocheng Li, Melvin Low et al.
Proceedings of the AAAI Conference on Artificial Intelligence
Stanford University
Deep Gaussian process with CNN or LSTM features predicts county-level crop yields from remote sensing; the target is agriculture, not weather or climate.
Applications & impactsClassic
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data
In one sentence. Deep Gaussian process with CNN or LSTM features predicts county-level crop yields from remote sensing; the target is agriculture, not weather or climate.
Labels
- Topic
- Applications & impacts
- Type
- New model or method
- Method
- CNN / U-Net, RNN / LSTM / ConvLSTM, GAN or VAE, Classical ML (trees, GP, linear, kernels)
- Domain
- Regional
- Data
- Satellite
- Status
- Research
- Identifiers
- DOI:10.1609/aaai.v31i1.11172 OpenAlex:W2604645045
- Added
- 2026-10-22
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