Flood Amateur Video for Semantic Segmentation Dataset

This dataset is flood data in the city of Parepare, South Sulawesi Province, which contains video data collected from social media Instagram. This dataset was created to develop deep learning methods for recognizing floods and surrounding objects, specializing in semantic segmentation methods. This...

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1. Verfasser: Intizhami, Naili Suri
Format: Dataset
Sprache:eng
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Zusammenfassung:This dataset is flood data in the city of Parepare, South Sulawesi Province, which contains video data collected from social media Instagram. This dataset was created to develop deep learning methods for recognizing floods and surrounding objects, specializing in semantic segmentation methods. This dataset consists of three folders, namely raw video data collected from Instagram, image data resulting from splitting the video into several images, and annotation data containing images that have been color-labeled according to their objects. There are 6 object classifications based on color labels, namely: floods (blue light), buildings (red), plants (green), people (sage), vehicles (orange), and sky (dark blue). This dataset has data in image (JPEG/PNG) and video (MP4) formats. This dataset is suitable for object recognition tasks with the semantic segmentation method. In addition, because this dataset contains original data in the form of videos and images, it can be developed for other purposes in the future. As a note, if you intend to use this dataset, please ensure that you comply with applicable copyright, privacy, and regulatory requirements. If you intend to read the paper about this dataset, please visit this link: https://doi.org/10.1016/j.dib.2023.109768
DOI:10.17632/3kzr8mt8s2