{"id":561,"date":"2025-07-14T20:46:28","date_gmt":"2025-07-14T20:46:28","guid":{"rendered":"https:\/\/ccds.ai\/?p=561"},"modified":"2025-08-10T18:15:11","modified_gmt":"2025-08-10T18:15:11","slug":"test-time-domain-adaptation-for-urban-categorization-from-satellite-images","status":"publish","type":"post","link":"https:\/\/ccds.ai\/?p=561","title":{"rendered":"Test-Time Domain Adaptation for Urban Categorization from Satellite Images"},"content":{"rendered":"<div id='av_section_1'  class='avia-section av-8s5lt-6803f2b5d9f7736591af37e86e97fc89 main_color avia-section-default avia-no-border-styling  avia-builder-el-0  avia-builder-el-no-sibling  avia-bg-style-scroll container_wrap fullsize'  ><div class='container av-section-cont-open' ><main  role=\"main\" itemprop=\"mainContentOfPage\"  class='template-page content  av-content-full alpha units'><div class='post-entry post-entry-type-page post-entry-561'><div class='entry-content-wrapper clearfix'>\n\n<style type=\"text\/css\" data-created_by=\"avia_inline_auto\" id=\"style-css-av-md3ktpca-a949e778eb3add054f1d27385b3eae49\">\n.avia-image-container.av-md3ktpca-a949e778eb3add054f1d27385b3eae49 img.avia_image{\nbox-shadow:none;\n}\n.avia-image-container.av-md3ktpca-a949e778eb3add054f1d27385b3eae49 .av-image-caption-overlay-center{\ncolor:#ffffff;\n}\n<\/style>\n<div  class='avia-image-container av-md3ktpca-a949e778eb3add054f1d27385b3eae49 av-styling- avia-align-center  avia-builder-el-1  el_before_av_textblock  avia-builder-el-first '   itemprop=\"image\" itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/ImageObject\" ><div class=\"avia-image-container-inner\"><div class=\"avia-image-overlay-wrap\"><img fetchpriority=\"high\" fetchpriority=\"high\" decoding=\"async\" class='wp-image-563 avia-img-lazy-loading-not-563 avia_image ' src=\"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/unnamed.jpg\" alt='' title='unnamed'  height=\"311\" width=\"512\"  itemprop=\"thumbnailUrl\" srcset=\"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/unnamed.jpg 512w, https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/unnamed-300x182.jpg 300w\" sizes=\"(max-width: 512px) 100vw, 512px\" \/><\/div><\/div><\/div>\n<section  class='av_textblock_section av-md3kpuow-c4f03ab4f78b4a079b27b988a228cb2d'  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/BlogPosting\" itemprop=\"blogPost\" ><div class='avia_textblock'  itemprop=\"text\" ><p>The urban environment is a complex system comprising various elements such as buildings, roads, vegetation, and water bodies. Classifying urban cities from satellite images or images captured by UAVs is an important task for urban planning, disaster management, and environmental monitoring. Urban environments differ across various cities of the world, and existing models for urban classification struggle to adapt to these changes. This project aims to develop an adaptive model for classifying urban cities from satellite images. This model will have the capability to generalize across different urban environments and adapt to the changing urban environment in real time. The model will be trained on a large dataset of satellite images of urban cities from different parts of the world. In inference or test time, the parameters of the model will be updated based on the changes in the different urban environments it has been deployed. This work will be built on recent work on Test time domain adaptation methods and our earlier research on the categorization of urban buildup [1], land usage, and land cover [2,3].<\/p>\n<p><strong>Related Works:<\/strong><\/p>\n<ol>\n<li aria-level=\"1\">Cheng, Q.; Zaber, M.; Rahman, A.M.; Zhang, H.; Guo, Z.; Okabe, A.; Shibasaki, R. Understanding the Urban Environment from Satellite Images with New Classification Method\u2014Focusing on Formality and Informality.\u00a0<i>Sustainability<\/i>\u00a0<b>2022<\/b>,\u00a0<i>14<\/i>, 4336. https:\/\/doi.org\/10.3390\/su14074336<\/li>\n<li aria-level=\"1\">Rahman, A.K.M.M.; Zaber, M.; Cheng, Q.; Nayem, A.B.S.; Sarker, A.; Paul, O.; Shibasaki, R. Applying State-of-the-Art Deep-Learning Methods to Classify Urban Cities of the Developing World.\u00a0<i>Sensors<\/i>\u00a0<b>2021<\/b>,\u00a0<i>21<\/i>, 7469.\u00a0<a href=\"https:\/\/web.archive.org\/web\/20250116235614\/https:\/\/doi.org\/10.3390\/s21227469\" target=\"_blank\" rel=\"noopener\">https:\/\/doi.org\/10.3390\/s21227469<\/a><\/li>\n<li aria-level=\"1\">Niloy, Fahim Faisal, et al. \u201cAttention toward neighbors: A context aware framework for high resolution image segmentation.\u201d\u00a0<i>2021 IEEE International Conference on Image Processing (ICIP)<\/i>. IEEE, 2021.<\/li>\n<\/ol>\n<\/div><\/section>\n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":563,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[90],"tags":[],"class_list":["post-561","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data_sci_projects"],"acf":[],"jetpack_featured_media_url":"https:\/\/ccds.ai\/wp-content\/uploads\/2025\/07\/unnamed.jpg","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/561","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=561"}],"version-history":[{"count":4,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/561\/revisions"}],"predecessor-version":[{"id":567,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/posts\/561\/revisions\/567"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=\/wp\/v2\/media\/563"}],"wp:attachment":[{"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=561"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=561"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/ccds.ai\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=561"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}