{"id":"https://openalex.org/W4417169516","doi":"https://doi.org/10.1109/tgrs.2025.3641926","title":"DGAT: Dynamic Gaussian Attenuate Transformer for Remote Sensing Image Change Captioning","display_name":"DGAT: Dynamic Gaussian Attenuate Transformer for Remote Sensing Image Change Captioning","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4417169516","doi":"https://doi.org/10.1109/tgrs.2025.3641926"},"language":null,"primary_location":{"id":"doi:10.1109/tgrs.2025.3641926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3641926","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032751984","display_name":"Pengfei Qin","orcid":"https://orcid.org/0000-0002-3357-433X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Pengfei Qin","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014312349","display_name":"Junmin Liu","orcid":"https://orcid.org/0000-0002-1462-7248"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junmin Liu","raw_affiliation_strings":["School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027174896","display_name":"Lanyu Li","orcid":"https://orcid.org/0000-0002-1596-2267"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lanyu Li","raw_affiliation_strings":["National Key Laboratory of Radar Detection and Sensing, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Key Laboratory of Radar Detection and Sensing, Nanjing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056902156","display_name":"Chao Tian","orcid":"https://orcid.org/0000-0003-4971-770X"},"institutions":[{"id":"https://openalex.org/I2801670068","display_name":"American Society for Photogrammetry and Remote Sensing","ror":"https://ror.org/041v7ky66","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I2801670068"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chao Tian","raw_affiliation_strings":["First Institute of Photogrammetry and Remote Sensing, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"First Institute of Photogrammetry and Remote Sensing, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I2801670068"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028103486","display_name":"Xiangyong Cao","orcid":"https://orcid.org/0000-0001-7912-3457"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyong Cao","raw_affiliation_strings":["School of Computer Science and Technology and the Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology and the Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]},{"raw_affiliation_string":"School of Computer Science and Technology, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032751984"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":1.0862,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.85399803,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.45969998836517334,"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":0.45969998836517334,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.14380000531673431,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.09160000085830688,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5866000056266785},{"id":"https://openalex.org/keywords/geospatial-analysis","display_name":"Geospatial analysis","score":0.5698999762535095},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.5511999726295471},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5311999917030334},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5131000280380249},{"id":"https://openalex.org/keywords/closed-captioning","display_name":"Closed captioning","score":0.474700003862381},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4580000042915344},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44130000472068787},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4375},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4284999966621399}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8111000061035156},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5866000056266785},{"id":"https://openalex.org/C9770341","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Geospatial analysis","level":2,"score":0.5698999762535095},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.5511999726295471},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5311999917030334},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5131000280380249},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5105999708175659},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4794999957084656},{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.474700003862381},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4580000042915344},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44130000472068787},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4375},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4284999966621399},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.38510000705718994},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3743000030517578},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C166550679","wikidata":"https://www.wikidata.org/wiki/Q263400","display_name":"Gaussian network model","level":3,"score":0.33899998664855957},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.32600000500679016},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3240000009536743},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32199999690055847},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3156999945640564},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.31119999289512634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.30970001220703125},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.3077000081539154},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.2985000014305115},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.29280000925064087},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C39399123","wikidata":"https://www.wikidata.org/wiki/Q1348989","display_name":"Earth observation","level":3,"score":0.27230000495910645},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.2689000070095062},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2574999928474426},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.2535000145435333}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3641926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3641926","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4210075541","display_name":null,"funder_award_id":"62276208","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4442529403","display_name":null,"funder_award_id":"U22B2059","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4976875354","display_name":null,"funder_award_id":"2024JC-JCQN-02","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G5817505303","display_name":null,"funder_award_id":"62272375","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6748661587","display_name":null,"funder_award_id":"12326607","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320336567","display_name":"Natural Science Basic Research Program of Shaanxi Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1956340063","https://openalex.org/W1973749534","https://openalex.org/W2033529478","https://openalex.org/W2101105183","https://openalex.org/W2108598243","https://openalex.org/W2112796928","https://openalex.org/W2194775991","https://openalex.org/W2752782242","https://openalex.org/W2896457183","https://openalex.org/W2963925437","https://openalex.org/W2965373594","https://openalex.org/W3027225766","https://openalex.org/W3138516171","https://openalex.org/W3180045188","https://openalex.org/W3203701986","https://openalex.org/W3205361185","https://openalex.org/W3207627484","https://openalex.org/W4211112734","https://openalex.org/W4211155378","https://openalex.org/W4221147537","https://openalex.org/W4226228401","https://openalex.org/W4289537913","https://openalex.org/W4313021481","https://openalex.org/W4362598957","https://openalex.org/W4378195019","https://openalex.org/W4385245566","https://openalex.org/W4386075553","https://openalex.org/W4387350510","https://openalex.org/W4387802245","https://openalex.org/W4388979610","https://openalex.org/W4390874378","https://openalex.org/W4391305855","https://openalex.org/W4396909912","https://openalex.org/W4398249074","https://openalex.org/W4400081502","https://openalex.org/W4400489056","https://openalex.org/W4402261590","https://openalex.org/W4402726980","https://openalex.org/W4402968170","https://openalex.org/W4403183405","https://openalex.org/W4403937461","https://openalex.org/W4405438806","https://openalex.org/W4407212099","https://openalex.org/W4408353959","https://openalex.org/W4408840974","https://openalex.org/W4414153662"],"related_works":[],"abstract_inverted_index":{"The":[0],"<italic":[1,123,134],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[2,124,135],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Remote":[3],"Sensing":[4],"Image":[5],"Change":[6],"Captioning</i>":[7],"(RSICC)":[8],"technique":[9],"is":[10],"designed":[11],"to":[12,45,49,66,108,141,170,213],"enhance":[13],"geospatial":[14],"analysis":[15],"by":[16,96],"generating":[17],"semantic":[18],"descriptions":[19],"of":[20,58,92,105,180,205,224,246],"differences":[21],"observed":[22],"in":[23,35,102,182],"bi-temporal":[24],"remote":[25],"sensing":[26],"imagery.":[27],"Although":[28],"Transformer-based":[29],"methods":[30,77],"have":[31],"achieved":[32],"significant":[33],"advancements":[34],"this":[36,119],"field,":[37],"their":[38],"standard":[39],"global":[40,80],"attention":[41,48,163,172,198],"mechanism":[42,140],"allows":[43],"pixels":[44],"pay":[46],"equal":[47],"all":[50],"spatial":[51,59,158],"positions,":[52,219],"which":[53,87,130],"lacks":[54],"explicit":[55],"prior":[56],"knowledge":[57],"proximity":[60],"correlation,":[61],"making":[62],"the":[63,90,97,103,111,116,157,178,186,191,196,202,222,244,247],"model":[64,142,253],"unable":[65],"strengthen":[67],"local":[68,183],"associations":[69],"and":[70,200,210,252],"weaken":[71],"long-distance":[72],"connections.":[73],"Furthermore,":[74],"most":[75],"existing":[76],"rely":[78],"on":[79,110,153,173,195,215,229],"average":[81],"pooling":[82,209],"when":[83],"reinforcing":[84],"channel-wise":[85],"representations,":[86],"often":[88],"dilutes":[89],"features":[91,216],"key":[93,218],"changed":[94],"regions":[95],"largely":[98],"unchanged":[99],"background,":[100],"resulting":[101],"inability":[104],"feature":[106],"compression":[107],"focus":[109,214],"critical":[112],"positions.":[113],"To":[114],"address":[115],"aforementioned":[117],"challenges,":[118],"paper":[120],"proposes":[121],"a":[122,133],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Dynamic":[125,136],"Gaussian":[126,137,166,207],"Attenuate":[127],"Transformer</i>":[128],"(DGAT),":[129],"innovatively":[131],"introduces":[132],"Attenuation</i>":[138],"(DGA)":[139],"an":[143],"attenuation":[144],"law":[145],"between":[146],"visual":[147,162,197],"tokens":[148],"from":[149],"two":[150],"perspectives":[151],"based":[152,194],"Euclidean":[154],"distance.":[155],"At":[156],"level,":[159,188],"DGA":[160,189,248],"constrains":[161],"through":[164],"distance-related":[165],"attenuation,":[167],"allowing":[168],"it":[169],"prioritize":[171],"adjacent":[174],"regions,":[175],"thereby":[176],"enhancing":[177,221],"detection":[179],"changes":[181],"continuity;":[184],"at":[185,217,257],"channel":[187,211],"identifies":[190],"core":[192],"area":[193],"kernel,":[199],"uses":[201],"joint":[203],"optimization":[204],"dynamic":[206],"weighted":[208],"modulation":[212],"effectively":[220],"expression":[223],"important":[225],"channels.":[226],"Experimental":[227],"results":[228],"three":[230],"benchmark":[231],"RSICC":[232],"datasets":[233],"demonstrate":[234],"that":[235],"our":[236],"proposed":[237],"DGAT":[238],"achieves":[239],"significantly":[240],"superior":[241],"results,":[242],"verifying":[243],"effectiveness":[245],"mechanism.":[249],"Our":[250],"code":[251],"weights":[254],"are":[255],"available":[256],"https://github.com/Pengfei1005/DGAT.":[258]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-12-09T00:00:00"}