hypelcnn:具有用于高光谱和激光雷达传感器数据的光谱和空间特征融合层的深度学习分类框架

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HypeLCNN概述 该存储库包含论文“具有用于高光谱和激光雷达传感器数据的光谱和空间特征融合层的深度学习分类框架”的论文源代码(正在审查中) 使用Tensorflow 1.x开发(在1.10至1.15版上测试)。 该存储库包括一套完整的套件,用于基于神经网络的高光谱和激光雷达分类。 主要特点: 支持超参数估计 基于插件的神经网络实现(通过NNModel接口) 基于插件的数据集集成(通过DataLoader接口) 培训的数据有效实现(基于内存的有效/基于内存/记录的) 能够在经典机器学习方法中使用数据集集成 神经网络的培训,分类和指标集成 胶囊网络和神经网络的示例实现 基于CPU / GPU / TPU(进行中)的培训 基于GAN的数据增强器集成 交叉折叠验证支持 源代码可用于在训练大数据集中应用张量流,集成指标,合并两个不同的神经网络以进行数据增强的最佳实践 注意:数据集文件太

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