{"id":"https://openalex.org/W3160423468","doi":"https://doi.org/10.3390/s21103483","title":"HADF-Crowd: A Hierarchical Attention-Based Dense Feature Extraction Network for Single-Image Crowd Counting","display_name":"HADF-Crowd: A Hierarchical Attention-Based Dense Feature Extraction Network for Single-Image Crowd Counting","publication_year":2021,"publication_date":"2021-05-17","ids":{"openalex":"https://openalex.org/W3160423468","doi":"https://doi.org/10.3390/s21103483","mag":"3160423468","pmid":"https://pubmed.ncbi.nlm.nih.gov/34067707"},"language":"en","primary_location":{"id":"doi:10.3390/s21103483","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21103483","pdf_url":"https://www.mdpi.com/1424-8220/21/10/3483/pdf?version=1621249275","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/21/10/3483/pdf?version=1621249275","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060351629","display_name":"Naveed Ilyas","orcid":"https://orcid.org/0000-0002-8220-4474"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Naveed Ilyas","raw_affiliation_strings":["Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082495705","display_name":"Boreom Lee","orcid":"https://orcid.org/0000-0002-7233-5833"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Boreom Lee","raw_affiliation_strings":["Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea","institution_ids":["https://openalex.org/I39534123"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050183146","display_name":"Kiseon Kim","orcid":"https://orcid.org/0000-0001-9166-0570"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kiseon Kim","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5082495705"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":1.0657,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.78766169,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"21","issue":"10","first_page":"3483","last_page":"3483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9930999875068665,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9908000230789185,"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/computer-science","display_name":"Computer science","score":0.7636094093322754},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.6761355996131897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6463041305541992},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6325670480728149},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5920480489730835},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5614087581634521},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5416103601455688},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5333715677261353},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5177885293960571},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5115319490432739},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.48651355504989624},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.45785224437713623},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45082753896713257},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3574464023113251},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25466930866241455}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7636094093322754},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6761355996131897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6463041305541992},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6325670480728149},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5920480489730835},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5614087581634521},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5416103601455688},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5333715677261353},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5177885293960571},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5115319490432739},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.48651355504989624},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.45785224437713623},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45082753896713257},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3574464023113251},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25466930866241455},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s21103483","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21103483","pdf_url":"https://www.mdpi.com/1424-8220/21/10/3483/pdf?version=1621249275","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:34067707","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34067707","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:1ef9f7f7249d4e759c0c94eca77539c3","is_oa":true,"landing_page_url":"https://doaj.org/article/1ef9f7f7249d4e759c0c94eca77539c3","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 21, Iss 10, p 3483 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/21/10/3483/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s21103483","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 21; Issue 10; Pages: 3483","raw_type":"Text"},{"id":"pmh:oai:pubmedcentral.nih.gov:8156381","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/8156381","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s21103483","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s21103483","pdf_url":"https://www.mdpi.com/1424-8220/21/10/3483/pdf?version=1621249275","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G2023063288","display_name":null,"funder_award_id":"9991006823","funder_id":"https://openalex.org/F4320318847","funder_display_name":"Korea Medical Device Development Fund"},{"id":"https://openalex.org/G573111460","display_name":null,"funder_award_id":"9991006823","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G617025228","display_name":null,"funder_award_id":"9991006823","funder_id":"https://openalex.org/F4320322014","funder_display_name":"Ministry of Food and Drug Safety"},{"id":"https://openalex.org/G8645528083","display_name":null,"funder_award_id":"9991006823","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"},{"id":"https://openalex.org/G992484961","display_name":null,"funder_award_id":"Korea","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320318847","display_name":"Korea Medical Device Development Fund","ror":null},{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320322014","display_name":"Ministry of Food and Drug Safety","ror":"https://ror.org/01f7dp456"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3160423468.pdf","grobid_xml":"https://content.openalex.org/works/W3160423468.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2168960788","https://openalex.org/W2463631526","https://openalex.org/W2560481731","https://openalex.org/W2740959624","https://openalex.org/W2741077351","https://openalex.org/W2745597836","https://openalex.org/W2788040570","https://openalex.org/W2792843139","https://openalex.org/W2792947308","https://openalex.org/W2798489385","https://openalex.org/W2798490576","https://openalex.org/W2798781811","https://openalex.org/W2799213142","https://openalex.org/W2808519136","https://openalex.org/W2810417872","https://openalex.org/W2810751829","https://openalex.org/W2833056938","https://openalex.org/W2884960332","https://openalex.org/W2887530227","https://openalex.org/W2888043458","https://openalex.org/W2915142517","https://openalex.org/W2919958344","https://openalex.org/W2949162858","https://openalex.org/W2952145882","https://openalex.org/W2954415862","https://openalex.org/W2962720716","https://openalex.org/W2963035940","https://openalex.org/W2963231953","https://openalex.org/W2963717945","https://openalex.org/W2964203052","https://openalex.org/W2964209782","https://openalex.org/W2964264515","https://openalex.org/W2965247173","https://openalex.org/W2967069910","https://openalex.org/W2969079301","https://openalex.org/W2969620138","https://openalex.org/W2970646403","https://openalex.org/W2970971581","https://openalex.org/W2976749699","https://openalex.org/W2978859332","https://openalex.org/W2981843652","https://openalex.org/W2981918755","https://openalex.org/W2982014038","https://openalex.org/W2982130202","https://openalex.org/W2990524248","https://openalex.org/W2991434406","https://openalex.org/W2995304495","https://openalex.org/W2995582330","https://openalex.org/W2996000181","https://openalex.org/W3098866279","https://openalex.org/W6775144507","https://openalex.org/W7006934443"],"related_works":["https://openalex.org/W3135697610","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W1647606319","https://openalex.org/W2922442631","https://openalex.org/W4390494008","https://openalex.org/W2053596378","https://openalex.org/W2964954556","https://openalex.org/W3088721469"],"abstract_inverted_index":{"Crowd":[0],"counting":[1,16,29,72,98,231,262],"is":[2,35,159,172,248],"a":[3,124],"challenging":[4],"task":[5,210],"due":[6,38],"to":[7,24,39,65,76,161,200,228,238,253,298],"large":[8,53,234],"perspective,":[9],"density,":[10],"and":[11,87,103,150,195,219,245,280],"scale":[12],"variations.":[13],"CNN-based":[14,70,125],"crowd":[15,28,71,132],"techniques":[17],"have":[18,266],"achieved":[19],"significant":[20],"performance":[21,283,296],"in":[22,30,57,96,101,233,292],"sparse":[23],"dense":[25,102,126,145,178,204],"environments.":[26],"However,":[27],"high":[31,97,104,230],"perspective-varying":[32,235],"scenes":[33],"(images)":[34],"getting":[36],"harder":[37],"different":[40],"density":[41],"levels":[42],"occupied":[43],"by":[44,215,223],"the":[45,58,216,240,251,268,285],"same":[46,59],"number":[47],"of":[48,174,209,284,294],"pixels.":[49],"In":[50,188,206],"this":[51,189],"way":[52,190],"variations":[54],"for":[55,130,260],"objects":[56],"spatial":[60],"area":[61],"make":[62],"it":[63],"difficult":[64],"count":[66],"accurately.":[67],"Further,":[68,107,237],"existing":[69],"methods":[73],"are":[74,84,113,198,226],"used":[75,85,160],"extract":[77],"rich":[78],"deep":[79],"features;":[80],"however,":[81],"these":[82,117],"features":[83,164,191,213,221,256],"locally":[86],"disseminated":[88],"while":[89],"propagating":[90],"through":[91,203],"intermediate":[92],"layers.":[93],"This":[94],"results":[95],"errors,":[99],"especially":[100],"perspective-variation":[105],"scenes.":[106,236],"class-specific":[108,241],"responses":[109],"along":[110,257],"channel":[111,152,258],"dimensions":[112,259],"underestimated.":[114],"To":[115],"address":[116],"above":[118],"mentioned":[119],"issues,":[120],"we":[121,265],"therefore":[122],"propose":[123],"feature":[127,146],"extraction":[128,147],"network":[129,158],"accurate":[131],"counting.":[133],"Our":[134],"proposed":[135,269,286],"model":[136],"comprises":[137],"three":[138,272],"main":[139],"modules:":[140],"(1)":[141],"backbone":[142,157],"network,":[143],"(2)":[144],"modules":[148,181,218],"(DFEMs),":[149],"(3)":[151],"attention":[153],"module":[154],"(CAM).":[155],"The":[156,170,282],"obtain":[162,229,254],"general":[163,212],"with":[165,185],"strong":[166],"transfer":[167],"learning":[168],"ability.":[169],"DFEM":[171],"composed":[173],"multiple":[175],"sub-modules":[176],"called":[177],"stacked":[179],"convolution":[180],"(DSCMs),":[182],"densely":[183],"connected":[184],"each":[186],"other.":[187],"extracted":[192],"from":[193],"lower":[194],"middle-lower":[196],"layers":[197,202],"propagated":[199],"higher":[201],"connections.":[205],"addition,":[207],"combinations":[208],"independent":[211],"obtained":[214,222],"former":[217],"task-specific":[220],"later":[224],"ones":[225],"incorporated":[227,249],"accuracy":[232],"exploit":[239],"response":[242],"between":[243],"background":[244],"foreground,":[246],"CAM":[247],"at":[250],"end":[252],"high-level":[255],"better":[261],"accuracy.":[263],"Moreover,":[264],"evaluated":[267],"method":[270],"on":[271],"well":[273],"known":[274],"datasets:":[275],"Shanghaitech":[276,278],"(Part-A),":[277],"(Part-B),":[279],"Venice.":[281],"technique":[287],"justifies":[288],"its":[289],"relative":[290],"effectiveness":[291],"terms":[293],"selected":[295],"compared":[297],"state-of-the-art":[299],"techniques.":[300]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
