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Aerial imagery analysis is critical for many research fields. However, obtaining frequent high-quality aerial images is not always accessible due to its high effort and cost requirements. One solution is to use the Ground-to-Aerial (G2A) technique to
Externí odkaz:
http://arxiv.org/abs/2408.04224
Publikováno v:
International Journal of COPD, Vol Volume 13, Pp 1207-1216 (2018)
Adnan Wshah,1,2 Sara JT Guilcher,2,3 Roger Goldstein,1,2,4,5 Dina Brooks1,2,5 1Respiratory Medicine, West Park Healthcare Centre, Toronto, ON, Canada; 2Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada; 3Leslie Dan Faculty
Externí odkaz:
https://doaj.org/article/247e335647c34d948eadc3ef370f25e2
Cross-View Geo-Localization (CVGL) estimates the location of a ground image by matching it to a geo-tagged aerial image in a database. Recent works achieve outstanding progress on CVGL benchmarks. However, existing methods still suffer from poor perf
Externí odkaz:
http://arxiv.org/abs/2308.09624
Cross-view geo-localization aims to estimate the location of a query ground image by matching it to a reference geo-tagged aerial images database. As an extremely challenging task, its difficulties root in the drastic view changes and different captu
Externí odkaz:
http://arxiv.org/abs/2212.04074
Cross-view geo-localization aims to estimate the GPS location of a query ground-view image by matching it to images from a reference database of geo-tagged aerial images. To address this challenging problem, recent approaches use panoramic ground-vie
Externí odkaz:
http://arxiv.org/abs/2210.14295
The concept of geo-localization refers to the process of determining where on earth some `entity' is located, typically using Global Positioning System (GPS) coordinates. The entity of interest may be an image, sequence of images, a video, satellite
Externí odkaz:
http://arxiv.org/abs/2112.15202
Publikováno v:
In Respiratory Medicine September 2024 231
Autor:
Wilson, Daniel, Alshaabi, Thayer, Van Oort, Colin, Zhang, Xiaohan, Nelson, Jonathan, Wshah, Safwan
Geo-localizing static objects from street images is challenging but also very important for road asset mapping and autonomous driving. In this paper we present a two-stage framework that detects and geolocalizes traffic signs from low frame rate stre
Externí odkaz:
http://arxiv.org/abs/2107.06257
recent literature has proposed various detection and identification methods for FDIAs, but few studies have focused on a solution that would prevent such attacks from occurring. However, great strides have been made using deep learning to detect atta
Externí odkaz:
http://arxiv.org/abs/2008.01330
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