随着深度学习图像分类每年变得越来越强大，很明显，将其引入灾难响应将提高响应者可以使用的效率。使用包括AlexNet，ResNet，MobileNet，DenseNets和4层CNN在内的几种神经网络模型，我们从大型图像数据集中对洪水灾害图像进行了分类，准确性高达79％。..

Train and Deploy an Image Classifier for Disaster Response

With Deep Learning Image Classification becoming more powerful each year, it is apparent that its introduction to disaster response will increase the efficiency that responders can work with. Using several Neural Network Models, including AlexNet, ResNet, MobileNet, DenseNets, and 4-Layer CNN, we have classified flood disaster images from a large image data set with up to 79% accuracy.Our models and tutorials for working with the data set have created a foundation for others to classify other types of disasters contained in the images.