FloodIMG: Flood image DataBase system.

ABSTRACT: A breakthrough in building models for image processing came with the discovery that a convolutional neural network (CNN) can progressively extract higher-level representations of the image content. Having high-resolution images to train CNN models is a key for optimizing the performance of image segmentation models. This paper presents a new dataset-called Flood Image (FloodIMG) database system-that was developed for flood related image processing and segmentation. We developed various Internet of Things Application Programming Interfaces (IoT API) to gather flood-related images from Twitter, and US federal agencies' web servers, such as the US Geological Survey (USGS) and the Department of Transportation (DOT). Overall, >9200 images of flooding events were collected, preprocessed, and for

SUBMITTER: Karanjit R 

PROVIDER: S-EPMC10164831 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature