Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region
| dc.contributor.author | Sarkar, Argho | |
| dc.contributor.author | Rahnemoonfar, Maryam | |
| dc.date.accessioned | 2023-04-12T17:22:00Z | |
| dc.date.available | 2023-04-12T17:22:00Z | |
| dc.date.issued | 2023-03-13 | |
| dc.description.abstract | 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. | en_US |
| dc.description.sponsorship | This work was supported by NSF BIGDATA Awards (IIS1838230, IIS-1947584), NSF HDR Institute Award (OAC2118285), IBM, and Amazon. We also acknowledge the support of the U.S. Army Grant No. W911NF2120076 | en_US |
| dc.description.uri | https://arxiv.org/abs/2303.07403 | en_US |
| dc.format.extent | 4 pages | en_US |
| dc.genre | journal articles | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m25psb-lmjw | |
| dc.identifier.uri | https://doi.org/10.48550/arXiv.2303.07403 | |
| dc.identifier.uri | http://hdl.handle.net/11603/27595 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
| dc.rights | Attribution 4.0 International (CC BY 4.0) | * |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
| dc.title | Polar-VQA: Visual Question Answering on Remote Sensed Ice sheet Imagery from Polar Region | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0002-8545-0830 | en_US |