{"id":"https://openalex.org/W4416756182","doi":"https://doi.org/10.1109/lgrs.2025.3633285","title":"A Multiscale Feature Refinement Detector for Small Objects With Ambiguous Boundaries","display_name":"A Multiscale Feature Refinement Detector for Small Objects With Ambiguous Boundaries","publication_year":2025,"publication_date":"2025-11-17","ids":{"openalex":"https://openalex.org/W4416756182","doi":"https://doi.org/10.1109/lgrs.2025.3633285"},"language":null,"primary_location":{"id":"doi:10.1109/lgrs.2025.3633285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3633285","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","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/A5014196571","display_name":"Weihua Shen","orcid":"https://orcid.org/0009-0002-5249-5175"},"institutions":[{"id":"https://openalex.org/I3129496460","display_name":"Lishui University","ror":"https://ror.org/0418kp584","country_code":"CN","type":"education","lineage":["https://openalex.org/I3129496460"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Shen","raw_affiliation_strings":["College of Artificial Intelligence, Lishui University, Lishui, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Artificial Intelligence, Lishui University, Lishui, Zhejiang, China","institution_ids":["https://openalex.org/I3129496460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005160474","display_name":"Yalin Li","orcid":"https://orcid.org/0009-0005-0053-6395"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalin Li","raw_affiliation_strings":["School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100428776","display_name":"Xiaohua Chen","orcid":"https://orcid.org/0000-0003-2646-2302"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohua Chen","raw_affiliation_strings":["School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0003-2646-2302","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101944979","display_name":"Chunzhi Li","orcid":"https://orcid.org/0000-0002-0402-6860"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chunzhi Li","raw_affiliation_strings":["School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China"],"raw_orcid":"https://orcid.org/0000-0002-0402-6860","affiliations":[{"raw_affiliation_string":"School of Information Engineering, Huzhou University, Huzhou, Zhejiang, China","institution_ids":["https://openalex.org/I3018263800"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32816989,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9236999750137329,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9236999750137329,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.014000000432133675,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.006399999838322401,"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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8895999789237976},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7946000099182129},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.6771000027656555},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6152999997138977},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5600000023841858},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5497999787330627},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5467000007629395},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5102999806404114},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4431000053882599}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8895999789237976},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7946000099182129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7712000012397766},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.6771000027656555},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6592000126838684},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6152999997138977},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5600000023841858},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5497999787330627},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5102999806404114},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4431000053882599},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4404999911785126},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.43700000643730164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4180000126361847},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4059999883174896},{"id":"https://openalex.org/C77052588","wikidata":"https://www.wikidata.org/wiki/Q644307","display_name":"Constant false alarm rate","level":2,"score":0.37599998712539673},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.36570000648498535},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2980000078678131},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.2815999984741211},{"id":"https://openalex.org/C106516650","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm design","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2651999890804291},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2025.3633285","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2025.3633285","pdf_url":null,"source":{"id":"https://openalex.org/S126920919","display_name":"IEEE Geoscience and Remote Sensing Letters","issn_l":"1545-598X","issn":["1545-598X","1558-0571"],"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 Geoscience and Remote Sensing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G269930907","display_name":null,"funder_award_id":"61501184","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W3018998681","https://openalex.org/W3171660447","https://openalex.org/W3182848941","https://openalex.org/W4294805043","https://openalex.org/W4396523238","https://openalex.org/W4396877674","https://openalex.org/W4400944113","https://openalex.org/W4405855034","https://openalex.org/W4406235068","https://openalex.org/W4406856734","https://openalex.org/W4407957024","https://openalex.org/W4408211783","https://openalex.org/W4408467392","https://openalex.org/W4409225100","https://openalex.org/W4410616160","https://openalex.org/W4410903002","https://openalex.org/W4411688622","https://openalex.org/W4412501412"],"related_works":[],"abstract_inverted_index":{"There":[0],"are":[1],"multiple":[2],"challenges":[3],"in":[4,110,116,128],"small":[5,79],"object":[6,42],"detection,":[7],"including":[8],"limited":[9],"instances,":[10],"insufficient":[11],"features,":[12],"diverse":[13],"scales,":[14],"uneven":[15],"distribution,":[16],"ambiguous":[17],"boundaries,":[18],"and":[19,31,35,57,76,112,124,144],"complex":[20],"backgrounds.":[21],"These":[22],"issues":[23],"often":[24],"lead":[25],"to":[26],"high":[27],"false":[28],"detection":[29,43,48,55,67,155],"rates":[30],"hinder":[32],"model":[33,136],"generalization":[34],"convergence.":[36],"This":[37],"study":[38],"proposes":[39],"a":[40,59,107,113,125],"multi-scale":[41],"algorithm":[44],"that":[45,103],"enhances":[46],"the":[47,54,82,119,131,135,138,145],"of":[49,78,140],"subtle":[50],"features":[51],"by":[52,90,142,148],"improving":[53],"head":[56,68],"incorporating":[58],"minimum":[60],"point":[61],"distance":[62],"intersection-over-union":[63],"loss.":[64],"The":[65],"enhanced":[66],"improves":[69],"target":[70],"representation,":[71],"enabling":[72],"more":[73],"precise":[74],"localization":[75],"classification":[77],"objects.":[80],"Meanwhile,":[81],"new":[83],"loss":[84],"function":[85],"stabilizes":[86],"bounding":[87,94],"box":[88,95],"regression":[89],"adaptively":[91],"adjusting":[92],"auxiliary":[93],"scales.":[96],"Evaluations":[97],"on":[98,118,130],"two":[99],"benchmark":[100],"datasets":[101],"demonstrate":[102],"our":[104],"method":[105],"achieves":[106],"2.6%":[108],"increase":[109,127],"mAP50":[111],"1.8%":[114],"improvement":[115],"mAP50:95":[117,129],"Satellite":[120],"Imagery":[121],"Multivehicles":[122],"dataset":[123],"1.9%":[126],"DIOR":[132],"dataset.":[133],"Furthermore,":[134],"reduces":[137],"number":[139],"parameters":[141],"2.5%":[143],"computational":[146],"cost":[147],"1.4%,":[149],"demonstrating":[150],"its":[151],"potential":[152],"for":[153],"real-time":[154],"applications.":[156]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-17T00:00:00"}