Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ...
For glaciologists, studying ice sheets from the polar regions is critical. With the advancement of deep learning techniques, we can now extract high-level information from the ice sheet data (e.g., estimating the ice layer thickness, predicting the ice accumulation for upcoming years, etc.). However...
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Online Access: | https://dx.doi.org/10.48550/arxiv.2303.07403 https://arxiv.org/abs/2303.07403 |
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ftdatacite:10.48550/arxiv.2303.07403 2023-05-15T16:39:52+02:00 Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... Sarkar, Argho Rahnemoonfar, Maryam 2023 https://dx.doi.org/10.48550/arxiv.2303.07403 https://arxiv.org/abs/2303.07403 unknown arXiv Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Computer Vision and Pattern Recognition cs.CV Artificial Intelligence cs.AI FOS Computer and information sciences Article article Preprint CreativeWork 2023 ftdatacite https://doi.org/10.48550/arxiv.2303.07403 2023-04-03T13:31:28Z For glaciologists, studying ice sheets from the polar regions is critical. With the advancement of deep learning techniques, we can now extract high-level information from the ice sheet data (e.g., estimating the ice layer thickness, predicting the ice accumulation for upcoming years, etc.). However, a vision-based conversational deep learning approach has not been explored yet, where scientists can get information by asking questions about images. In this paper, we have introduced the task of Visual Question Answering (VQA) on remote-sensed ice sheet imagery. To study, we have presented a unique VQA dataset, Polar-VQA, in this study. All the images in this dataset were collected using four types of airborne radars. The main objective of this research is to highlight the importance of VQA in the context of ice sheet research and conduct a baseline study of existing VQA approaches on Polar-VQA dataset. ... Article in Journal/Newspaper Ice Sheet DataCite Metadata Store (German National Library of Science and Technology) |
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Open Polar |
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DataCite Metadata Store (German National Library of Science and Technology) |
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topic |
Computer Vision and Pattern Recognition cs.CV Artificial Intelligence cs.AI FOS Computer and information sciences |
spellingShingle |
Computer Vision and Pattern Recognition cs.CV Artificial Intelligence cs.AI FOS Computer and information sciences Sarkar, Argho Rahnemoonfar, Maryam Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
topic_facet |
Computer Vision and Pattern Recognition cs.CV Artificial Intelligence cs.AI FOS Computer and information sciences |
description |
For glaciologists, studying ice sheets from the polar regions is critical. With the advancement of deep learning techniques, we can now extract high-level information from the ice sheet data (e.g., estimating the ice layer thickness, predicting the ice accumulation for upcoming years, etc.). However, a vision-based conversational deep learning approach has not been explored yet, where scientists can get information by asking questions about images. In this paper, we have introduced the task of Visual Question Answering (VQA) on remote-sensed ice sheet imagery. To study, we have presented a unique VQA dataset, Polar-VQA, in this study. All the images in this dataset were collected using four types of airborne radars. The main objective of this research is to highlight the importance of VQA in the context of ice sheet research and conduct a baseline study of existing VQA approaches on Polar-VQA dataset. ... |
format |
Article in Journal/Newspaper |
author |
Sarkar, Argho Rahnemoonfar, Maryam |
author_facet |
Sarkar, Argho Rahnemoonfar, Maryam |
author_sort |
Sarkar, Argho |
title |
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
title_short |
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
title_full |
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
title_fullStr |
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
title_full_unstemmed |
Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region ... |
title_sort |
polar-vqa: visual question answering on remote sensed ice sheet imagery from polar region ... |
publisher |
arXiv |
publishDate |
2023 |
url |
https://dx.doi.org/10.48550/arxiv.2303.07403 https://arxiv.org/abs/2303.07403 |
genre |
Ice Sheet |
genre_facet |
Ice Sheet |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.48550/arxiv.2303.07403 |
_version_ |
1766030215787577344 |