arXiv AI
Multi-Step Forecasting of Grape Berry Temperature based on LSTM Model with Feed-Forward Attention
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Exploratory Analysis of Deep Learning Models for Forecasting Meteorological Parameters in the Agricultural Sector
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A Sequence-to-Sequence ConvLSTM Approach for Leaf Area Index Forecasting over the South-Central United States
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Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling
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Leaf Spectral Reflectance Prediction Using Multi-Head Attention Neural Networks
arXiv:2606. 01432v1 Announce Type: new Abstract: Accurate modeling of leaf spectral reflectance from physiological and biochemical traits is essential for advancing remote sensing applications in plant science and precision agriculture.
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A Hybrid LSTM--Vision Transformer Architecture for Predicting HRRR Forecast Errors
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Calibrating Biophysical Models for Grape Phenology Prediction via Multi-Task Learning
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