{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T17:16:26Z","timestamp":1777569386255,"version":"3.51.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8]]},"abstract":"<jats:p>Despite recent progress in computer vision, fine-grained interpretation of satellite images remains challenging because of a lack of labeled training data. To overcome this limitation, we construct a novel dataset called WikiSatNet by pairing geo-referenced Wikipedia articles with satellite imagery of their corresponding locations. We then propose two strategies to learn representations of satellite images by predicting properties of the corresponding articles from the images. Leveraging this new multi-modal dataset, we can drastically reduce the quantity of human-annotated labels and time required for downstream tasks. On the recently released fMoW dataset, our pre-training strategies can boost the performance of a model pre-trained on ImageNet by up to\u00a04.5%\u00a0in F1 score.<\/jats:p>","DOI":"10.24963\/ijcai.2019\/502","type":"proceedings-article","created":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:46:05Z","timestamp":1564299965000},"page":"3620-3626","source":"Crossref","is-referenced-by-count":20,"title":["Learning to Interpret Satellite Images using Wikipedia"],"prefix":"10.24963","author":[{"given":"Burak","family":"Uzkent","sequence":"first","affiliation":[{"name":"Department of Computer Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Evan","family":"Sheehan","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chenlin","family":"Meng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongyi","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Earth Systems Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marshall","family":"Burke","sequence":"additional","affiliation":[{"name":"Department of Earth Systems Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Lobell","sequence":"additional","affiliation":[{"name":"Department of Earth Systems Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefano","family":"Ermon","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Stanford University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"name":"Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}","theme":"Artificial Intelligence","location":"Macao, China","acronym":"IJCAI-2019","number":"28","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2019,8,10]]},"end":{"date-parts":[[2019,8,16]]}},"container-title":["Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2019,7,28]],"date-time":"2019-07-28T07:49:45Z","timestamp":1564300185000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2019\/502"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2019,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2019\/502","relation":{},"subject":[],"published":{"date-parts":[[2019,8]]}}}