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Recognising place under distinct weather variability, a comparison between end-to-end and metric learning approaches.

, , , , and . IV, page 1360-1365. IEEE, (2022)

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Why Is Greenwich so Common? Quantifying the Uniqueness of Multivariate Observations (Short Paper)., and . GIScience, volume 277 of LIPIcs, page 15:1-15:6. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2023)The Data Hungry Home., , , , , and . HTTF, page 6:1-6:10. ACM, (2019)A Scalable Analytical Framework for Spatio-Temporal Analysis of Neighborhood Change: A Sequence Analysis Approach., , and . AGILE Conference, page 223-241. Springer, (2019)What Can We Expect from Navigating?: Exploring Navigation, Wearables and Data Through Critical Design Concepts., , , , , and . Conference on Designing Interactive Systems (Companion Volume), page 237-244. ACM, (2019)Mapping Trusted Paths to VGI., , , and . IPAW, volume 12839 of Lecture Notes in Computer Science, page 207-210. Springer, (2021)Quantifying Geospatial in the Common Crawl Corpus., , , and . CoRR, (2024)Recognising place under distinct weather variability, a comparison between end-to-end and metric learning approaches., , , , and . IV, page 1360-1365. IEEE, (2022)Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?, , , , and . GeoExT@ECIR, volume 3683 of CEUR Workshop Proceedings, page 91-105. CEUR-WS.org, (2024)CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl., , , and . CoRR, (2024)