{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,24]],"date-time":"2025-09-24T00:14:50Z","timestamp":1758672890849,"version":"3.44.0"},"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":[[2025,9]]},"abstract":"<jats:p>Flood extent mapping is crucial for disaster response and damage assessment. While Earth imagery and terrain data (in the form of DEM) are now readily available, there are few flood annotation data for training machine learning models, which hinders the automated mapping of flooded areas. We propose ALFA, an interactive active-learning-based approach to minimize the annotators' efforts when preparing the ground-truth flood map in a satellite image. ALFA calibrates the prediction consistency of a segmentation model (1) across training cycles and (2) for various data augmentations. The two consistencies are integrated into the design of both the acquisition function and the loss function to enhance the robustness of active learning with limited annotation inputs. ALFA recommends those superpixels that the underlying model is most uncertain about, and users can annotate their pixels with minimal clicks with the help of elevation guidance. Extensive experiments on various regions hit by flooding show that we can improve the annotation time from hours to around 20 minutes. ALFA is open sourced at https:\/\/github.com\/saugatadhikari\/alfa.<\/jats:p>","DOI":"10.24963\/ijcai.2025\/1057","type":"proceedings-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:10:40Z","timestamp":1758269440000},"page":"9511-9519","source":"Crossref","is-referenced-by-count":0,"title":["Faster Annotation for Elevation-Guided Flood Extent Mapping by Consistency-Enhanced Active Learning"],"prefix":"10.24963","author":[{"given":"Saugat","family":"Adhikari","sequence":"first","affiliation":[{"name":"Indiana University Bloomington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Da","family":"Yan","sequence":"additional","affiliation":[{"name":"Indiana University Bloomington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyang","family":"Wang","sequence":"additional","affiliation":[{"name":"University of Alabama at Birmingham"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Landon","family":"Dyken","sequence":"additional","affiliation":[{"name":"University of Illinois Chicago"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sidharth","family":"Kumar","sequence":"additional","affiliation":[{"name":"University of Illinois Chicago"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lyuheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"Indiana University Bloomington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akhlaque","family":"Ahmad","sequence":"additional","affiliation":[{"name":"Indiana University Bloomington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiao","family":"Han","sequence":"additional","affiliation":[{"name":"Indiana University Bloomington"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yang","family":"Zhou","sequence":"additional","affiliation":[{"name":"Auburn University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Steve","family":"Petruzza","sequence":"additional","affiliation":[{"name":"Utah State University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"10584","event":{"number":"34","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2025","name":"Thirty-Fourth International Joint Conference on Artificial Intelligence {IJCAI-25}","start":{"date-parts":[[2025,8,16]]},"theme":"Artificial Intelligence","location":"Montreal, Canada","end":{"date-parts":[[2025,8,22]]}},"container-title":["Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,9,23]],"date-time":"2025-09-23T11:35:59Z","timestamp":1758627359000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2025\/1057"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2025,9]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2025\/1057","relation":{},"subject":[],"published":{"date-parts":[[2025,9]]}}}