{"id":"https://openalex.org/W4416250489","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229288","title":"SCSNet: Semantic segmentation of carbon source and sink in remote sensing images based on multi-scale transformer and local feature fusion","display_name":"SCSNet: Semantic segmentation of carbon source and sink in remote sensing images based on multi-scale transformer and local feature fusion","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250489","doi":"https://doi.org/10.1109/ijcnn64981.2025.11229288"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11229288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229288","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-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/A5041220862","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7018-646X"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004"],"affiliations":[{"raw_affiliation_string":"Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109713037","display_name":"Wenqian Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenqian Cao","raw_affiliation_strings":["Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004"],"affiliations":[{"raw_affiliation_string":"Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5117396941","display_name":"H. Xu","orcid":"https://orcid.org/0000-0002-2786-0954"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haige Xu","raw_affiliation_strings":["Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004"],"affiliations":[{"raw_affiliation_string":"Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000730473","display_name":"Yaqin Xie","orcid":"https://orcid.org/0000-0003-2266-023X"},"institutions":[{"id":"https://openalex.org/I173899330","display_name":"Henan University","ror":"https://ror.org/003xyzq10","country_code":"CN","type":"education","lineage":["https://openalex.org/I173899330"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Xie","raw_affiliation_strings":["Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004"],"affiliations":[{"raw_affiliation_string":"Henan University,Henan Key Laboratory of Big Data Analysis and Processing,Kaifeng,China,475004","institution_ids":["https://openalex.org/I173899330"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113413996","display_name":"Changwei Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210111792","display_name":"Guizhou Water Conservancy and Hydropower Survey and Design Institute","ror":"https://ror.org/026z6mp76","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210111792"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changwei Miao","raw_affiliation_strings":["Nuclear Industry Survey Design & Research Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Nuclear Industry Survey Design & Research Co., Ltd","institution_ids":["https://openalex.org/I4210111792"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5041220862"],"corresponding_institution_ids":["https://openalex.org/I173899330"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.48838318,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.42809998989105225,"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":0.42809998989105225,"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":0.20909999310970306,"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/T14413","display_name":"Advanced Technologies in Various Fields","score":0.061799999326467514,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/segmentation","display_name":"Segmentation","score":0.7807999849319458},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5227000117301941},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5151000022888184},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.44699999690055847},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.37130001187324524},{"id":"https://openalex.org/keywords/remote-sensing-application","display_name":"Remote sensing application","score":0.350600004196167},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.349700003862381}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7807999849319458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7127000093460083},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6413000226020813},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5307000279426575},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5227000117301941},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5151000022888184},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44920000433921814},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.44699999690055847},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.37130001187324524},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.350600004196167},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.34790000319480896},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.34150001406669617},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3395000100135803},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.33160001039505005},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.26919999718666077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11229288","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11229288","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2155632266","https://openalex.org/W2398730140","https://openalex.org/W2560023338","https://openalex.org/W2787091153","https://openalex.org/W2799213142","https://openalex.org/W2950925862","https://openalex.org/W2963857746","https://openalex.org/W3034427230","https://openalex.org/W3093432062","https://openalex.org/W3109998321","https://openalex.org/W3110440461","https://openalex.org/W3161825146","https://openalex.org/W3176839087","https://openalex.org/W3200075728","https://openalex.org/W4205346899","https://openalex.org/W4283450732","https://openalex.org/W4285301526","https://openalex.org/W4289752563","https://openalex.org/W4312443924","https://openalex.org/W4385245566","https://openalex.org/W4386634500","https://openalex.org/W4386825170","https://openalex.org/W4391878073","https://openalex.org/W4396909873"],"related_works":[],"abstract_inverted_index":{"Achieving":[0],"carbon":[1,4,19,21,45,88,246,255,258],"peak":[2],"and":[3,47,49,68,90,111,120,198,206,224,244,248,257],"neutrality":[5],"is":[6,185,264],"a":[7,79,117,129,213],"major":[8],"strategic":[9],"goal":[10],"for":[11,83,254],"China.":[12],"With":[13],"the":[14,41,96,105,125,140,163,174,181,190,204],"gradual":[15],"expansion":[16],"of":[17,33,44,87,99,107,166,177,208,216],"China's":[18],"market,":[20],"monitoring":[22,256],"plays":[23],"an":[24],"increasingly":[25],"significant":[26],"role":[27],"in":[28,73,124,153,236],"support":[29,253],"services.":[30],"Semantic":[31],"segmentation":[32,66,74,81,97,175,234,240],"high-resolution":[34],"remote":[35,60,84,100,154,237],"sensing":[36,61,85,101,155,238],"images":[37,62,86,102,156],"can":[38],"effectively":[39],"capture":[40,134],"spatial":[42],"distribution":[43],"sources":[46,89,247],"sinks":[48],"their":[50],"dynamic":[51],"changes":[52],"by":[53,103,193],"accurately":[54,242],"dividing":[55],"land":[56],"cover":[57],"types.":[58],"However,":[59],"often":[63],"have":[64],"complex":[65],"boundaries":[67],"numerous":[69],"small-scale":[70,178],"targets,":[71],"resulting":[72],"difficulties.":[75],"This":[76],"paper":[77,211],"proposes":[78],"semantic":[80,196],"network":[82],"sinks,":[91,249],"SCSNet,":[92,209],"aiming":[93],"to":[94,133,142,149,171],"optimize":[95],"effect":[98],"combining":[104],"ability":[106,141],"multi-scale":[108,130],"feature":[109,147],"modeling":[110],"local":[112,146],"detail":[113,200],"capturing.":[114],"SCSNet":[115,231],"uses":[116],"Multi-scale":[118],"Self-attention":[119],"Local":[121],"Aggregation":[122],"module":[123],"decoder,":[126],"which":[127,187],"introduces":[128],"self-attention":[131],"mechanism":[132],"global":[135],"contextual":[136],"information":[137,192,197],"while":[138],"enhancing":[139],"perceive":[143],"details":[144],"through":[145],"aggregation":[148],"distinguish":[150],"similar":[151],"targets":[152],"effectively.":[157],"The":[158,226],"Feature":[159,182],"Fusion":[160],"Module":[161,184],"realizes":[162],"effective":[164],"fusion":[165],"features":[167],"at":[168,266],"different":[169],"scales":[170],"further":[172,188],"enhance":[173],"accuracy":[176],"targets.":[179],"Additionally,":[180],"Refinement":[183],"introduced,":[186],"refines":[189],"boundary":[191],"fusing":[194],"high-level":[195],"low-level":[199],"features.":[201],"To":[202],"validate":[203],"effectiveness":[205],"superiority":[207],"this":[210],"conducts":[212],"large":[214],"number":[215],"experiments":[217],"on":[218],"public":[219],"datasets,":[220],"including":[221],"LoveDA,":[222],"Vaihingen,":[223],"Potsdam.":[225],"experimental":[227],"results":[228],"show":[229],"that":[230],"achieves":[232],"advanced":[233],"performance":[235],"image":[239],"tasks,":[241],"identifying":[243],"differentiating":[245],"thus":[250],"providing":[251],"powerful":[252],"emission":[259],"assessment.":[260],"Our":[261],"source":[262],"code":[263],"available":[265],"https://github.com/SCS123-LAB/SCSNet.":[267]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}