{"id":"https://openalex.org/W4408862710","doi":"https://doi.org/10.1109/icce63647.2025.10930036","title":"Tiny Objects Classification on Remote Sensing Image by Using Multi-Scale Crop","display_name":"Tiny Objects Classification on Remote Sensing Image by Using Multi-Scale Crop","publication_year":2025,"publication_date":"2025-01-11","ids":{"openalex":"https://openalex.org/W4408862710","doi":"https://doi.org/10.1109/icce63647.2025.10930036"},"language":"en","primary_location":{"id":"doi:10.1109/icce63647.2025.10930036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","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/A5111116990","display_name":"R. Su","orcid":"https://orcid.org/0009-0004-9331-0311"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Rou-Ying Su","raw_affiliation_strings":["National Taiwan University of Science and Technology,Electronic and Computer Engineering Department,Taipei,Taiwan,R.O.C"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Electronic and Computer Engineering Department,Taipei,Taiwan,R.O.C","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009788338","display_name":"Pei\u2010Jun Lee","orcid":"https://orcid.org/0000-0003-2010-0853"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Pei-Jun Lee","raw_affiliation_strings":["National Taiwan University of Science and Technology,Electronic and Computer Engineering Department,Taipei,Taiwan,R.O.C"],"affiliations":[{"raw_affiliation_string":"National Taiwan University of Science and Technology,Electronic and Computer Engineering Department,Taipei,Taiwan,R.O.C","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5111116990"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.12664205,"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":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8700000047683716,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.8700000047683716,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.6561943292617798},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6427117586135864},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6029279232025146},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5127769112586975},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5032760500907898},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47575873136520386},{"id":"https://openalex.org/keywords/crop","display_name":"Crop","score":0.4577540159225464},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4128267168998718},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.320435106754303},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21853971481323242},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1633223593235016},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1482672095298767}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6561943292617798},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6427117586135864},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029279232025146},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5127769112586975},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5032760500907898},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47575873136520386},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.4577540159225464},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4128267168998718},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.320435106754303},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21853971481323242},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1633223593235016},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1482672095298767},{"id":"https://openalex.org/C97137747","wikidata":"https://www.wikidata.org/wiki/Q38112","display_name":"Forestry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icce63647.2025.10930036","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icce63647.2025.10930036","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Consumer Electronics (ICCE)","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":1,"referenced_works":["https://openalex.org/W4312443924"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2059707233","https://openalex.org/W1983126463","https://openalex.org/W2085738998","https://openalex.org/W2139939267","https://openalex.org/W1974511032"],"abstract_inverted_index":{"Classifying":[0],"tiny":[1,37],"objects":[2],"in":[3],"remote":[4],"sensing":[5],"images":[6],"(e.g.,":[7],"a":[8,13,18,24],"20x20":[9],"pixels":[10],"target":[11,51],"within":[12],"resolution":[14],"1000x1000":[15],"image)":[16],"is":[17],"significant":[19],"challenge.":[20],"This":[21,53],"paper":[22],"adopts":[23],"fused":[25],"FPN":[26],"(Feature":[27],"Pyramid":[28],"Network)":[29],"to":[30],"enhance":[31],"the":[32,40,50],"feature":[33],"extraction":[34],"capability":[35],"for":[36],"objects.":[38,52],"Additionally,":[39],"proposed":[41],"multi-scale":[42],"crop":[43],"method":[44],"can":[45],"more":[46],"effectively":[47],"focus":[48],"on":[49],"network":[54],"architecture":[55],"improves":[56],"overall":[57],"accuracy":[58],"by":[59],"14.4%.":[60]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}
