{"id":"https://openalex.org/W4401879386","doi":"https://doi.org/10.1109/lgrs.2024.3449872","title":"Hybrid Network Based on Hierarchical Multipatch Feature Encoder for Infrared Small Target Detection","display_name":"Hybrid Network Based on Hierarchical Multipatch Feature Encoder for Infrared Small Target Detection","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401879386","doi":"https://doi.org/10.1109/lgrs.2024.3449872"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2024.3449872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3449872","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/A5047990019","display_name":"In Ho Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"In Ho Lee","raw_affiliation_strings":["Department of Aerospace Engineering, Automation and Systems Research Institute, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-6186-4879","affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054791152","display_name":"Chan Gook Park","orcid":"https://orcid.org/0000-0002-7403-951X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chan Gook Park","raw_affiliation_strings":["Department of Aerospace Engineering, Automation and Systems Research Institute, Seoul National University, Seoul, South Korea"],"raw_orcid":"https://orcid.org/0000-0002-7403-951X","affiliations":[{"raw_affiliation_string":"Department of Aerospace Engineering, Automation and Systems Research Institute, Seoul National University, Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":2.4773,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.91517874,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":"21","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9876000285148621,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.659103512763977},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6165598630905151},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.608007550239563},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.4173974096775055},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40463149547576904},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36367228627204895},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10044872760772705},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09171748161315918}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.659103512763977},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6165598630905151},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.608007550239563},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.4173974096775055},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40463149547576904},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36367228627204895},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10044872760772705},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09171748161315918},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2024.3449872","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2024.3449872","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/G186211556","display_name":null,"funder_award_id":"UD230014SD","funder_id":"https://openalex.org/F4320334874","funder_display_name":"Defense Acquisition Program Administration"}],"funders":[{"id":"https://openalex.org/F4320334874","display_name":"Defense Acquisition Program Administration","ror":"https://ror.org/04bjg9m96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2150815919","https://openalex.org/W3015788359","https://openalex.org/W3094502228","https://openalex.org/W3118249006","https://openalex.org/W3127751679","https://openalex.org/W3138516171","https://openalex.org/W3171950886","https://openalex.org/W4312827004","https://openalex.org/W4313855947","https://openalex.org/W4376478071","https://openalex.org/W4376607843","https://openalex.org/W4386157344","https://openalex.org/W4388266680"],"related_works":["https://openalex.org/W4390516098","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W2142795561","https://openalex.org/W4205302943","https://openalex.org/W2561132942","https://openalex.org/W3155418658","https://openalex.org/W4243199227","https://openalex.org/W2033914206","https://openalex.org/W2042327336"],"abstract_inverted_index":{"With":[0],"recent":[1],"advances":[2],"in":[3,19,80,135,155],"artificial":[4],"intelligence,":[5],"deep":[6],"learning":[7],"networks":[8],"with":[9,186,197],"various":[10],"structures":[11],"are":[12],"being":[13,65],"applied":[14],"to":[15,34,67,73,102,120,129,161],"target":[16,23,183],"detection.":[17],"However,":[18,60],"the":[20,55,61,69,74,92,106,140,147,163],"infrared":[21],"small":[22,96],"detection":[24,184],"(IRSTD)":[25],"field,":[26],"an":[27,88,152],"appropriate":[28],"network":[29,108],"structure":[30,113],"is":[31,78,195,203],"still":[32],"required":[33],"identify":[35],"blurry":[36],"and":[37,47,98,124,173,190,192],"low-contrast":[38],"targets":[39],"accurately.":[40],"Conventional":[41],"U-net":[42,178],"algorithms":[43],"use":[44],"skip":[45],"connection":[46],"attention":[48,174],"module":[49],"because":[50],"information":[51,123,132,142],"loss":[52,148],"occurs":[53],"as":[54],"convolution":[56,77],"layer":[57],"becomes":[58],"deeper.":[59],"problem":[62],"of":[63,76],"not":[64],"able":[66],"recognize":[68],"entire":[70],"image":[71,93],"due":[72],"limitations":[75],"fatal":[79],"IRSTD.":[81],"To":[82,137],"overcome":[83],"these":[84],"limitations,":[85],"we":[86],"design":[87],"encoder":[89,112,119,128],"that":[90,114],"divides":[91],"into":[94],"multiple":[95],"pieces":[97],"stacks":[99],"them":[100],"hierarchically":[101],"extract":[103,121,130],"features.":[104],"Therefore,":[105],"proposed":[107,167],"has":[109,157],"a":[110,116,125],"hybrid":[111,164],"combines":[115],"convolution-based":[117],"multiscale":[118,175],"local":[122],"hierarchical-based":[126],"multipatch":[127,171],"global":[131],"by":[133],"running":[134],"parallel.":[136],"effectively":[138],"fuse":[139],"hierarchical":[141,170],"obtained":[143],"from":[144],"each":[145],"layer,":[146],"function,":[149],"which":[150],"plays":[151],"important":[153],"role":[154],"learning,":[156],"also":[158],"been":[159],"changed":[160],"suit":[162],"encoder.":[165],"The":[166],"algorithm,":[168],"named":[169],"feature":[172,176],"fusion":[177],"(HMAMFU-net),":[179],"can":[180],"guarantee":[181],"effective":[182],"performance":[185,193],"two":[187],"datasets:":[188],"NUDT-SIRST":[189],"NUAA-SIRST,":[191],"analysis":[194],"conducted":[196],"other":[198],"state-of-the-art":[199],"algorithms.":[200],"PyTorch":[201],"implementation":[202],"available":[204],"at":[205],"<uri":[206],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[207],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/skylih87/HMAMFU-net</uri>.":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
