{"id":"https://openalex.org/W4386590839","doi":"https://doi.org/10.1109/lgrs.2023.3314026","title":"NAS-Kernel: Learning Suitable Gaussian Kernel for Remote-Sensing Object Counting","display_name":"NAS-Kernel: Learning Suitable Gaussian Kernel for Remote-Sensing Object Counting","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4386590839","doi":"https://doi.org/10.1109/lgrs.2023.3314026"},"language":"en","primary_location":{"id":"doi:10.1109/lgrs.2023.3314026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3314026","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/A5101988654","display_name":"Liangliang Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Liangliang Zhao","raw_affiliation_strings":["School of Artificial Intelligence, and the OPtics and ElectroNics (iOPEN), School of Computer Science, Northwestern Polytechnical University, Xi&#x2019;an, China","School of Computer Science, Northwestern Polytechnical University, Xi'an, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, and the OPtics and ElectroNics (iOPEN), School of Computer Science, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical University, Xi'an, P. R. China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001848378","display_name":"Junyu Gao","orcid":"https://orcid.org/0000-0001-6000-8168"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I890469752","display_name":"Ministry of Industry and Information Technology","ror":"https://ror.org/0385nmy68","country_code":"CN","type":"government","lineage":["https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyu Gao","raw_affiliation_strings":["School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Xi'an, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Xi'an, P. R. China","institution_ids":["https://openalex.org/I890469752"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106943753","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0003-2924-946X"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]},{"id":"https://openalex.org/I890469752","display_name":"Ministry of Industry and Information Technology","ror":"https://ror.org/0385nmy68","country_code":"CN","type":"government","lineage":["https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["School of Artificial Intelligence, and the OPtics and ElectroNics (iOPEN), School of Computer Science, Northwestern Polytechnical University, Xi&#x2019;an, China","Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Xi'an, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, and the OPtics and ElectroNics (iOPEN), School of Computer Science, Northwestern Polytechnical University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I17145004"]},{"raw_affiliation_string":"Key Laboratory of Intelligent Interaction and Applications, Ministry of Industry and Information Technology, Xi'an, P. R. China","institution_ids":["https://openalex.org/I890469752"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101988654"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":1.5647,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.85483576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"20","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9995999932289124,"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":0.9987000226974487,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.625969648361206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6107720136642456},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5789262056350708},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5217384099960327},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.49069106578826904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4849012494087219},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.4721177816390991},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.44756168127059937},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4302799105644226},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.4279894232749939},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.426056444644928},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41279250383377075},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32687026262283325},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2943706512451172},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.24816927313804626},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1288059949874878}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.625969648361206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6107720136642456},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5789262056350708},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5217384099960327},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.49069106578826904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4849012494087219},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.4721177816390991},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.44756168127059937},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4302799105644226},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.4279894232749939},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.426056444644928},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41279250383377075},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32687026262283325},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2943706512451172},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.24816927313804626},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1288059949874878},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lgrs.2023.3314026","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lgrs.2023.3314026","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/G5135811258","display_name":null,"funder_award_id":"2022ZD0160400","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2463631526","https://openalex.org/W2914974653","https://openalex.org/W2922295717","https://openalex.org/W2945574898","https://openalex.org/W2962720716","https://openalex.org/W2963136578","https://openalex.org/W2963693541","https://openalex.org/W2964095233","https://openalex.org/W2964209782","https://openalex.org/W2967069910","https://openalex.org/W2982130202","https://openalex.org/W3042011474","https://openalex.org/W3082834645","https://openalex.org/W3084883754","https://openalex.org/W3089024309","https://openalex.org/W3138516171","https://openalex.org/W3185344366","https://openalex.org/W3201018943","https://openalex.org/W3201518019","https://openalex.org/W4288287245","https://openalex.org/W4293168762","https://openalex.org/W4365799088","https://openalex.org/W4384519099","https://openalex.org/W6759443934","https://openalex.org/W6764825297"],"related_works":["https://openalex.org/W1973746459","https://openalex.org/W2089892314","https://openalex.org/W2095626363","https://openalex.org/W2169565408","https://openalex.org/W1603091392","https://openalex.org/W2121506664","https://openalex.org/W2369557298","https://openalex.org/W2545232906","https://openalex.org/W2375370983","https://openalex.org/W2011212036"],"abstract_inverted_index":{"The":[0,164],"purpose":[1],"of":[2,10,13,110,123,177,185],"object":[3,26,40],"counting":[4,27,41,57,70,146],"is":[5,134,157],"to":[6,29,89,106,115,121,159],"estimate":[7],"the":[8,64,78,90,108,127,169,175,182,189,196,199,218],"number":[9],"specific":[11],"kinds":[12],"objects":[14,122],"in":[15,25,47,77,97,126,142],"a":[16,73,135,150],"given":[17],"image.":[18],"In":[19,101,148],"remote":[20,98],"sensing":[21,99],"imagery,":[22],"challenges":[23,91],"arise":[24],"due":[28],"issues":[30],"like":[31],"scale":[32,94],"variations":[33,95],"and":[34,58,61,204,211],"complex":[35],"backgrounds.":[36],"Existing":[37],"density":[38,68,79,129,144],"map-based":[39,69,145],"methods":[42,71],"have":[43,62],"achieved":[44],"satisfactory":[45],"performance":[46,176],"some":[48],"general":[49],"scenarios":[50],"(":[51],"<italic":[52],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[53],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i.e</i>":[54],".,":[55],"crowd":[56],"vehicle":[59],"counting)":[60],"become":[63],"mainstream":[65],"methods.":[66,147,220],"These":[67],"use":[72,107],"fixed":[74],"Gaussian":[75,118,128],"kernel":[76],"map":[80,130],"generation":[81,131],"stage,":[82],"thus":[83],"they":[84],"are":[85],"not":[86],"well":[87],"adapted":[88],"such":[92],"as":[93],"present":[96],"scenes.":[100],"this":[102],"letter,":[103],"we":[104],"propose":[105],"strategy":[109,156],"neural":[111],"architecture":[112],"search":[113],"(NAS-Kernel)":[114],"select":[116],"appropriate":[117],"kernels":[119],"corresponding":[120],"different":[124],"scales":[125],"stage.":[132],"NAS-Kernel":[133],"plug-and-play":[136],"algorithm":[137],"that":[138,168,188],"can":[139,172],"be":[140],"used":[141],"other":[143],"addition,":[149],"contextual":[151],"path":[152],"aggregation":[153],"feature":[154,162],"fusion":[155],"proposed":[158,170,190,200],"fuse":[160],"multi-scale":[161],"information.":[163],"ablation":[165],"experiments":[166],"verify":[167],"method":[171,191,201],"significantly":[173],"improve":[174],"baseline.":[178],"Experimental":[179],"results":[180],"on":[181],"four":[183],"sub-datasets":[184],"RSOC":[186],"show":[187],"achieves":[192,202],"state-of-the-art":[193],"performance.":[194],"On":[195],"Building":[197],"sub-dataset,":[198],"18%":[203],"12%":[205],"lower":[206],"Mean":[207,213],"Absolute":[208],"Error":[209,215],"(MAE)":[210],"Root":[212],"Square":[214],"(RMSE)":[216],"than":[217],"existing":[219]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}