Dataset for flood area recognition with semantic segmentation

Floods are natural disasters that repeatedly occur in Indonesia, causing substantial material losses and claiming many lives. Meanwhile, social media data has emerged as a valuable resource for analyzing user behaviour and interests, and its use for flood-related information is increasing. In this p...

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Main Authors: Naili Suri Intizhami, Eka Qadri Nuranti, Nur Inaya Bahar
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Data in Brief
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340923008351
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author Naili Suri Intizhami
Eka Qadri Nuranti
Nur Inaya Bahar
author_facet Naili Suri Intizhami
Eka Qadri Nuranti
Nur Inaya Bahar
author_sort Naili Suri Intizhami
collection DOAJ
description Floods are natural disasters that repeatedly occur in Indonesia, causing substantial material losses and claiming many lives. Meanwhile, social media data has emerged as a valuable resource for analyzing user behaviour and interests, and its use for flood-related information is increasing. In this paper, we present a flood dataset collected from Instagram Reels, which consists of videos depicting flood events in Parepare. Every video was collected from different areas, time conditions and viewpoint, and converted into image form. The data set includes 7248 images. Images undergo preprocessing to ensure a clear depiction and differentiation of the flood event from the surrounding elements. Annotations given to each object, using a different color label, facilitate recognition and understanding of various computer vision applications. Overall, this flood dataset is a valuable resource for computer vision research, especially semantic segmentation method and promotes the development of algorithms for flood area identification and object recognition in flood-affected areas.
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spelling doaj.art-f067ed3e7cc94eb685aca7f518deb11f2023-12-02T07:00:23ZengElsevierData in Brief2352-34092023-12-0151109768Dataset for flood area recognition with semantic segmentationNaili Suri Intizhami0Eka Qadri Nuranti1Nur Inaya Bahar2Corresponding author.; Institut Teknologi Bacharuddin Jusuf Habibie, IndonesiaInstitut Teknologi Bacharuddin Jusuf Habibie, IndonesiaInstitut Teknologi Bacharuddin Jusuf Habibie, IndonesiaFloods are natural disasters that repeatedly occur in Indonesia, causing substantial material losses and claiming many lives. Meanwhile, social media data has emerged as a valuable resource for analyzing user behaviour and interests, and its use for flood-related information is increasing. In this paper, we present a flood dataset collected from Instagram Reels, which consists of videos depicting flood events in Parepare. Every video was collected from different areas, time conditions and viewpoint, and converted into image form. The data set includes 7248 images. Images undergo preprocessing to ensure a clear depiction and differentiation of the flood event from the surrounding elements. Annotations given to each object, using a different color label, facilitate recognition and understanding of various computer vision applications. Overall, this flood dataset is a valuable resource for computer vision research, especially semantic segmentation method and promotes the development of algorithms for flood area identification and object recognition in flood-affected areas.http://www.sciencedirect.com/science/article/pii/S2352340923008351FloodSemantic segmentationVideoObject detectionImage
spellingShingle Naili Suri Intizhami
Eka Qadri Nuranti
Nur Inaya Bahar
Dataset for flood area recognition with semantic segmentation
Data in Brief
Flood
Semantic segmentation
Video
Object detection
Image
title Dataset for flood area recognition with semantic segmentation
title_full Dataset for flood area recognition with semantic segmentation
title_fullStr Dataset for flood area recognition with semantic segmentation
title_full_unstemmed Dataset for flood area recognition with semantic segmentation
title_short Dataset for flood area recognition with semantic segmentation
title_sort dataset for flood area recognition with semantic segmentation
topic Flood
Semantic segmentation
Video
Object detection
Image
url http://www.sciencedirect.com/science/article/pii/S2352340923008351
work_keys_str_mv AT nailisuriintizhami datasetforfloodarearecognitionwithsemanticsegmentation
AT ekaqadrinuranti datasetforfloodarearecognitionwithsemanticsegmentation
AT nurinayabahar datasetforfloodarearecognitionwithsemanticsegmentation