{"id":"https://openalex.org/W7161982942","doi":"https://doi.org/10.3390/rs18101673","title":"POCA-Lite: A Lightweight Change-Detection Architecture with Geometry-Aware Auxiliary Supervision and Feedback Fusion","display_name":"POCA-Lite: A Lightweight Change-Detection Architecture with Geometry-Aware Auxiliary Supervision and Feedback Fusion","publication_year":2026,"publication_date":"2026-05-21","ids":{"openalex":"https://openalex.org/W7161982942","doi":"https://doi.org/10.3390/rs18101673"},"language":"en","primary_location":{"id":"doi:10.3390/rs18101673","doi":"https://doi.org/10.3390/rs18101673","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18101673","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/rs18101673","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5048859101","display_name":"Yongqi Shi","orcid":"https://orcid.org/0000-0003-0950-3600","observed_orcids":["https://orcid.org/0000-0003-0950-3600"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqi Shi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124718428","display_name":"Ruopeng Yang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ruopeng Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121245127","display_name":"Bo Huang","orcid":"https://orcid.org/0009-0000-6229-9587","observed_orcids":["https://orcid.org/0009-0000-6229-9587"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Huang","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0000-6229-9587","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068271805","display_name":"Zhaoyang Gu","orcid":"https://orcid.org/0000-0002-9650-5462","observed_orcids":["https://orcid.org/0000-0002-9650-5462","https://orcid.org/0009-0000-3991-0253","https://orcid.org/0000-0002-7660-8085"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoyang Gu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041134721","display_name":"Yiwei Lu","orcid":"https://orcid.org/0000-0002-0791-2964","observed_orcids":["https://orcid.org/0000-0002-0791-2964","https://orcid.org/0009-0001-4806-5167"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yiwei Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5121275060","display_name":"Changsheng Yin","orcid":"https://orcid.org/0000-0003-0730-6830","observed_orcids":["https://orcid.org/0000-0003-0730-6830"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changsheng Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036128504","display_name":"Yongqi Wen","orcid":"https://orcid.org/0009-0007-8421-1372","observed_orcids":["https://orcid.org/0009-0007-8421-1372"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongqi Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5078354232","display_name":"Yihao Zhong","orcid":"https://orcid.org/0009-0003-5348-4184","observed_orcids":["https://orcid.org/0009-0003-5348-4184"]},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yihao Zhong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2700,"currency":"CHF","value_usd":3258},"apc_paid":{"value":2700,"currency":"CHF","value_usd":3258},"fwci":6.3831,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.96555244,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"18","issue":"10","first_page":"1673","last_page":"1673"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.0,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/change-detection","display_name":"change detection","score":0.9639999866485596},{"id":"https://openalex.org/keywords/distance-transform","display_name":"distance transform","score":0.8460000157356262},{"id":"https://openalex.org/keywords/boundary-prediction","display_name":"boundary prediction","score":0.6610000133514404},{"id":"https://openalex.org/keywords/cross-dataset-transfer","display_name":"cross-dataset transfer","score":0.7760000228881836},{"id":"https://openalex.org/keywords/levir-cd","display_name":"LEVIR-CD","score":0.8619999885559082},{"id":"https://openalex.org/keywords/whu-cd","display_name":"WHU-CD","score":0.9430000185966492},{"id":"https://openalex.org/keywords/urban-change-detection","display_name":"urban change detection","score":0.5270000100135803}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7372000217437744},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6328999996185303},{"id":"https://openalex.org/C2778712577","wikidata":"https://www.wikidata.org/wiki/Q3505966","display_name":"Retraining","level":2,"score":0.5580999851226807},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.5475000143051147},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.4487000107765198},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4221999943256378},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4187000095844269},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.41749998927116394},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.39890000224113464},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.3725999891757965},{"id":"https://openalex.org/C124681953","wikidata":"https://www.wikidata.org/wiki/Q339062","display_name":"Decomposition","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3070000112056732},{"id":"https://openalex.org/C2781234732","wikidata":"https://www.wikidata.org/wiki/Q943505","display_name":"Fusion center","level":4,"score":0.3003000020980835},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29089999198913574},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2711000144481659},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2687000036239624},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.26109999418258667},{"id":"https://openalex.org/C2778844933","wikidata":"https://www.wikidata.org/wiki/Q630950","display_name":"Interlocking","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2551000118255615}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs18101673","doi":"https://doi.org/10.3390/rs18101673","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18101673","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"doi:10.20944/preprints202604.1523.v1","doi":"https://doi.org/10.20944/preprints202604.1523.v1","is_oa":true,"landing_page_url":"https://doi.org/10.20944/preprints202604.1523.v1","pdf_url":null,"source":{"id":"https://openalex.org/S6309402219","display_name":"Preprints.org","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"},{"id":"pmh:oai:doaj.org/article:65be322a733a43f1aaaac77bf475a1d8","doi":null,"is_oa":true,"landing_page_url":"https://doaj.org/article/65be322a733a43f1aaaac77bf475a1d8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 18, Iss 10, p 1673 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs18101673","doi":"https://doi.org/10.3390/rs18101673","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs18101673","pdf_url":null,"source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7250000238418579,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"sustainable_development_goals_aurora":[{"score":0.7655771970748901,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Building":[0],"change":[1,187],"detection":[2,188],"from":[3],"bi-temporal":[4],"remote-sensing":[5],"imagery":[6],"underpins":[7],"urban":[8,166],"planning,":[9],"infrastructure":[10],"monitoring,":[11],"and":[12,51,69,95,168],"disaster":[13],"assessment.":[14],"Existing":[15],"deep-learning":[16],"methods":[17],"achieve":[18],"high":[19],"accuracy":[20],"but":[21,195],"rely":[22],"on":[23,156,164,189],"large":[24],"parameter":[25],"counts,":[26],"while":[27,90,125],"pixel-level":[28],"supervision":[29,117,181],"provides":[30],"limited":[31],"boundary":[32],"guidance.":[33],"We":[34],"propose":[35],"POCA-lite,":[36],"a":[37,62,76,141],"lightweight":[38],"encoder\u2013decoder":[39],"with":[40,191],"an":[41],"inference-coupled":[42,179],"geometry":[43],"branch:":[44],"three":[45],"geometric":[46,116,180],"prediction":[47],"heads\u2014distance":[48],"transform,":[49],"boundary,":[50],"center":[52],"heatmap\u2014whose":[53],"outputs":[54],"are":[55],"fused":[56],"back":[57],"into":[58],"the":[59,72,106,122,126,135,160],"decoder":[60],"via":[61],"feedback":[63,127],"pathway":[64,129],"active":[65],"at":[66],"both":[67],"training":[68],"inference.":[70],"On":[71],"LEVIR-CD":[73],"benchmark":[74],"under":[75],"unified":[77],"retraining":[78],"protocol,":[79],"multi-seed":[80],"evaluation":[81,155],"shows":[82,158],"that":[83,159,178],"POCA-lite":[84],"matches":[85],"SNUNet":[86,148,163],"in":[87],"mean":[88],"F1":[89,100],"using":[91],"47%":[92],"fewer":[93,97],"parameters":[94],"53%":[96],"FLOPs.":[98],"Boundary":[99],"improves":[101],"by":[102],"9.22":[103],"pp":[104,151],"over":[105],"no-geometry":[107],"baseline.":[108],"Decomposition":[109],"ablations":[110],"reveal":[111],"two":[112],"complementary":[113],"improvement":[114],"sources:":[115],"alone":[118],"recovers":[119,130],"85%":[120],"of":[121],"total":[123],"gain,":[124],"fusion":[128],"92%;":[131],"their":[132],"combination":[133],"achieves":[134],"full":[136],"result.":[137],"Geometry-aware":[138],"targets":[139],"outperform":[140],"generic":[142],"multitask":[143],"control.":[144],"Cross-architecture":[145],"transfer":[146,171],"to":[147],"yields":[149],"+1.06":[150],"F1.":[152],"However,":[153],"cross-dataset":[154,170],"WHU-CD":[157],"method":[161],"underperforms":[162],"dense":[165],"morphology,":[167,194],"zero-shot":[169],"is":[172,182,198],"not":[173],"established.":[174],"These":[175],"results":[176],"indicate":[177],"effective":[183],"for":[184],"lightweight,":[185],"boundary-sensitive":[186],"domains":[190],"well-separated":[192],"building":[193],"its":[196],"applicability":[197],"scope-bounded.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-10-17T09:40:24.721904","created_date":"2026-05-22T00:00:00"}
