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MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer

Created2025-02-04|Updated2025-02-04
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Author: ALTNT
Link: http://blog.705553939.xyz/2025/02/04/crop_classification/Crop%20classification/2023-MMST-ViT/
Copyright Notice: All articles in this blog are licensed under CC BY-NC-SA 4.0 unless stating additionally.
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Contents
  1. 1. MMST-ViT: Climate Change-aware Crop Yield Prediction via Multi-Modal Spatial-Temporal Vision Transformer
    1. 1.1. 摘要
    2. 1.2. 介绍
    3. 1.3. 2.相关工作
      1. 1.3.1. Vision Transformer。
      2. 1.3.2. Deep Learning (DL) for Crop Yield Prediction。
    4. 1.4. 3、数据集
      1. 1.4.1. 美国农业部作物数据集。
      2. 1.4.2. HRRR Computed dataset。
      3. 1.4.3. Sentinel-2影像。
    5. 1.5. 4、方法
      1. 1.5.1. 4.1 问题陈述
      2. 1.5.2. 4.2 挑战
      3. 1.5.3. 4.3 本文提出的方法
        1. 1.5.3.1. 模型概述
        2. 1.5.3.2. 多模态transformer
        3. 1.5.3.3. 空间 transformer
        4. 1.5.3.4. 时间transformer
    6. 1.6. 5、实验
      1. 1.6.1. 5.1 实验设置
        1. 1.6.1.1. 数据集
        2. 1.6.1.2. 对比方法
        3. 1.6.1.3. 评估指标
        4. 1.6.1.4. 模型大小
        5. 1.6.1.5. 超参数
      2. 1.6.2. 5.2. 比较性能评估
      3. 1.6.3. 5.3.可视化作物产量预测误差
      4. 1.6.4. 5.4. 一年期预测的表现
      5. 1.6.5. 5.5. 消融研究
        1. 1.6.5.1. 关键组件
        2. 1.6.5.2. 预训练技术
    7. 1.7. 代码
      1. 1.7.1. 生成配置文件
      2. 1.7.2. 调试main_pretrain_mmst_vit.py
      3. 1.7.3. 对于哨兵二号数据
      4. 1.7.4. WRF-HRRR 计算数据集
      5. 1.7.5. USDA Crop Dataset
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