{"id":"https://openalex.org/W4412536574","doi":"https://doi.org/10.1109/tgrs.2025.3591260","title":"Multiscale Gaussian Attention Mechanism for Tiny-Object Detection in Remote Sensing Images","display_name":"Multiscale Gaussian Attention Mechanism for Tiny-Object Detection in Remote Sensing Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412536574","doi":"https://doi.org/10.1109/tgrs.2025.3591260"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3591260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3591260","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/A5102701991","display_name":"Shuohao Shi","orcid":"https://orcid.org/0009-0003-4254-7637"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuohao Shi","raw_affiliation_strings":["College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055651722","display_name":"Qiang Fang","orcid":"https://orcid.org/0000-0002-5063-6889"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiang Fang","raw_affiliation_strings":["College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053112608","display_name":"Xin Xu","orcid":"https://orcid.org/0000-0003-3238-745X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Xu","raw_affiliation_strings":["College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006729432","display_name":"Dezun Dong","orcid":"https://orcid.org/0000-0001-6243-8479"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dezun Dong","raw_affiliation_strings":["College of Computer Science, National University of Defense Technology, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, National University of Defense Technology, Changsha, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5102701991"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":15.0066,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.98405658,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9532999992370605,"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":0.9532999992370605,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9426000118255615,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9253000020980835,"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/remote-sensing","display_name":"Remote sensing","score":0.630508303642273},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5805283188819885},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5796260237693787},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4980196952819824},{"id":"https://openalex.org/keywords/mechanism","display_name":"Mechanism (biology)","score":0.4731277823448181},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46154123544692993},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.45655977725982666},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4308394193649292},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4177086651325226},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.30642732977867126},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2602660655975342},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1577780544757843}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.630508303642273},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5805283188819885},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5796260237693787},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4980196952819824},{"id":"https://openalex.org/C89611455","wikidata":"https://www.wikidata.org/wiki/Q6804646","display_name":"Mechanism (biology)","level":2,"score":0.4731277823448181},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46154123544692993},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.45655977725982666},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4308394193649292},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4177086651325226},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.30642732977867126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2602660655975342},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1577780544757843},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3591260","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3591260","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":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":89,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2193145675","https://openalex.org/W2194775991","https://openalex.org/W2479866714","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2752782242","https://openalex.org/W2795812085","https://openalex.org/W2807183728","https://openalex.org/W2922509574","https://openalex.org/W2924873663","https://openalex.org/W2928165649","https://openalex.org/W2934198733","https://openalex.org/W2963150697","https://openalex.org/W2963351448","https://openalex.org/W2963474687","https://openalex.org/W2963857746","https://openalex.org/W2964093967","https://openalex.org/W2964241181","https://openalex.org/W2982770724","https://openalex.org/W2986357608","https://openalex.org/W2988452521","https://openalex.org/W2991359031","https://openalex.org/W3012573144","https://openalex.org/W3014641072","https://openalex.org/W3034429256","https://openalex.org/W3034552520","https://openalex.org/W3041525128","https://openalex.org/W3046838151","https://openalex.org/W3096609285","https://openalex.org/W3121020412","https://openalex.org/W3125509312","https://openalex.org/W3138516171","https://openalex.org/W3160733999","https://openalex.org/W3162240418","https://openalex.org/W3172752666","https://openalex.org/W3175630421","https://openalex.org/W3177257155","https://openalex.org/W3205100603","https://openalex.org/W3212386989","https://openalex.org/W4283717190","https://openalex.org/W4288325606","https://openalex.org/W4289752563","https://openalex.org/W4294982749","https://openalex.org/W4295123323","https://openalex.org/W4313172897","https://openalex.org/W4319778298","https://openalex.org/W4378652798","https://openalex.org/W4379928223","https://openalex.org/W4382568144","https://openalex.org/W4384519088","https://openalex.org/W4385800738","https://openalex.org/W4385804923","https://openalex.org/W4389076493","https://openalex.org/W4391559729","https://openalex.org/W4392157793","https://openalex.org/W4392543375","https://openalex.org/W4392667193","https://openalex.org/W4393171204","https://openalex.org/W4393207085","https://openalex.org/W4393906060","https://openalex.org/W4399416251","https://openalex.org/W4400188498","https://openalex.org/W4400350735","https://openalex.org/W4400485728","https://openalex.org/W4400727870","https://openalex.org/W4401387435","https://openalex.org/W4401433267","https://openalex.org/W4402716047","https://openalex.org/W4402727675","https://openalex.org/W4403888306","https://openalex.org/W4404855392","https://openalex.org/W4405022379","https://openalex.org/W4406049673","https://openalex.org/W4406728173","https://openalex.org/W6637373629","https://openalex.org/W6737664043","https://openalex.org/W6750227808","https://openalex.org/W6760424586","https://openalex.org/W6762718338","https://openalex.org/W6766978945","https://openalex.org/W6767892146","https://openalex.org/W6784094891","https://openalex.org/W6798838024","https://openalex.org/W6802878479","https://openalex.org/W6809665764","https://openalex.org/W6868582632","https://openalex.org/W6870504892"],"related_works":["https://openalex.org/W2382997850","https://openalex.org/W2390968135","https://openalex.org/W2382213751","https://openalex.org/W2351750670","https://openalex.org/W1597848696","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W1964286703","https://openalex.org/W2169866437","https://openalex.org/W3056417032"],"abstract_inverted_index":{"Tiny":[0],"object":[1,32,43,57,61,170],"detection":[2,33,44,171],"is":[3,182],"increasingly":[4],"crucial":[5],"in":[6,50,55],"the":[7,53,92,174],"fields":[8,82,94,132],"such":[9],"as":[10],"remote":[11],"sensing,":[12],"traffic":[13],"monitoring,":[14],"and":[15,64,110,137,149,176],"robotics.":[16],"Inspired":[17],"by":[18,95],"human":[19],"visual":[20],"perception,":[21],"attention":[22,37,71,85,140],"mechanism":[23,128,155],"has":[24],"become":[25],"a":[26,120,138],"widely":[27],"used":[28],"method":[29],"for":[30],"enhancing":[31],"performance.":[34],"While":[35],"existing":[36],"mechanisms":[38,72],"have":[39],"significantly":[40],"advanced":[41],"general":[42],"performance,":[45],"they":[46,100],"often":[47,101],"fall":[48],"short":[49],"adapting":[51],"to":[52,83,90,107,146],"characteristics":[54],"tiny":[56],"datasets,":[58],"including":[59],"huge":[60],"size":[62],"variations":[63],"concentrated":[65],"distributions.":[66],"In":[67,152],"detailed,":[68],"most":[69],"current":[70],"rely":[73],"on":[74,168],"convolutional":[75,144],"or":[76],"linear":[77],"layers":[78,145],"with":[79,133],"fixed":[80],"receptive":[81,93,131],"compute":[84],"vectors.":[86],"Some":[87],"methods":[88],"attempt":[89],"enlarge":[91],"using":[96],"multiscale":[97,130],"structures,":[98],"but":[99],"simply":[102],"sum":[103],"feature":[104,135],"maps,":[105],"leading":[106],"information":[108],"interference":[109],"increased":[111],"computational":[112],"costs.":[113],"To":[114],"address":[115],"these":[116],"issues,":[117],"we":[118],"propose":[119],"novel":[121],"Multiscale":[122],"Gaussian":[123,139],"Attention":[124],"Mechanism":[125],"(MGAM).":[126],"This":[127],"integrates":[129],"dynamic":[134],"weighting":[136],"module,":[141],"replacing":[142],"traditional":[143],"reduce":[147],"training":[148],"inference":[150],"overhead.":[151],"additional,":[153],"our":[154,179],"can":[156],"be":[157],"easily":[158],"embedded":[159],"into":[160],"various":[161],"detectors":[162],"without":[163],"any":[164],"hyperparameters.":[165],"Extensive":[166],"experiments":[167],"six":[169],"datasets":[172],"demonstrate":[173],"effectiveness":[175],"robustness":[177],"of":[178],"method.":[180],"Code":[181],"available":[183],"at:":[184],"https://github.com/cszzshi/MGAM.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
