论文标题
屋顶材料分类
Roof material classification from aerial imagery
论文作者
论文摘要
本文介绍了一种使用航拍照片分类的算法。算法的主要优势是提高预测准确性的拟议方法。提出的方法包括：转换神经网络的影像网的方法，用于使用多通道图像；除了对神经网络的特定预测外，还使用了第二级模型的特殊特征；特殊的图像增强集以提高训练准确性。此外，提出了解决此问题的完整流程。以下内容可在开放访问中可用：解决方案代码，权重集和使用的神经网络的体系结构。拟议的解决方案在比赛“开放AI加勒比挑战赛”中获得了第二名。
This paper describes an algorithm for classification of roof materials using aerial photographs. Main advantages of the algorithm are proposed methods to improve prediction accuracy. Proposed methods includes: method of converting ImageNet weights of neural networks for using multi-channel images; special set of features of second level models that are used in addition to specific predictions of neural networks; special set of image augmentations that improve training accuracy. In addition, complete flow for solving this problem is proposed. The following content is available in open access: solution code, weight sets and architecture of the used neural networks. The proposed solution achieved second place in the competition "Open AI Caribbean Challenge".
