{"id":"https://openalex.org/W3024906006","doi":"https://doi.org/10.1109/access.2020.2993570","title":"Multi-Scale Convolutional Features Network for Semantic Segmentation in Indoor Scenes","display_name":"Multi-Scale Convolutional Features Network for Semantic Segmentation in Indoor Scenes","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3024906006","doi":"https://doi.org/10.1109/access.2020.2993570","mag":"3024906006"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2993570","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2993570","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09090817.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09090817.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101689857","display_name":"Yanran Wang","orcid":"https://orcid.org/0000-0001-5881-5016"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanran Wang","raw_affiliation_strings":["Jinan University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016292021","display_name":"Qingliang Chen","orcid":"https://orcid.org/0000-0001-5849-8268"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingliang Chen","raw_affiliation_strings":["Guangzhou Xuanyuan Research Institute Company, Ltd., Guangzhou, China","Jinan University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Xuanyuan Research Institute Company, Ltd., Guangzhou, China","institution_ids":[]},{"raw_affiliation_string":"Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080761979","display_name":"Shilang Chen","orcid":"https://orcid.org/0000-0002-0891-5956"},"institutions":[{"id":"https://openalex.org/I14894300","display_name":"Foshan University","ror":"https://ror.org/02xvvvp28","country_code":"CN","type":"education","lineage":["https://openalex.org/I14894300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shilang Chen","raw_affiliation_strings":["School of Mechatronics Engineering, Foshan University, Foshan, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronics Engineering, Foshan University, Foshan, China","institution_ids":["https://openalex.org/I14894300"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5057893502","display_name":"Junjun Wu","orcid":"https://orcid.org/0000-0003-3534-0673"},"institutions":[{"id":"https://openalex.org/I14894300","display_name":"Foshan University","ror":"https://ror.org/02xvvvp28","country_code":"CN","type":"education","lineage":["https://openalex.org/I14894300"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjun Wu","raw_affiliation_strings":["School of Mechatronics Engineering, Foshan University, Foshan, China"],"affiliations":[{"raw_affiliation_string":"School of Mechatronics Engineering, Foshan University, Foshan, China","institution_ids":["https://openalex.org/I14894300"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101689857"],"corresponding_institution_ids":["https://openalex.org/I159948400"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.3928,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.60950496,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"8","issue":null,"first_page":"89575","last_page":"89583"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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":0.8329086303710938},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8267485499382019},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7141431570053101},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7081191539764404},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5906786918640137},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5324711799621582},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48036274313926697},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4749617278575897},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47274526953697205},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.45680636167526245},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4394414722919464},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4392998218536377},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.18178588151931763}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8329086303710938},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8267485499382019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7141431570053101},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7081191539764404},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5906786918640137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5324711799621582},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48036274313926697},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4749617278575897},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47274526953697205},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.45680636167526245},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4394414722919464},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4392998218536377},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.18178588151931763},{"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2993570","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2993570","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09090817.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:756024b4dc844a7d961a55ecaa672397","is_oa":true,"landing_page_url":"https://doaj.org/article/756024b4dc844a7d961a55ecaa672397","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":"IEEE Access, Vol 8, Pp 89575-89583 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2993570","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2993570","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09090817.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1121271761","display_name":null,"funder_award_id":"Program","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1438299633","display_name":null,"funder_award_id":"2018KZDXM074","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1477544716","display_name":null,"funder_award_id":"Guangdong","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1522606338","display_name":null,"funder_award_id":"2019KZDZX1026","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3435950671","display_name":null,"funder_award_id":"and Gr","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G418610320","display_name":null,"funder_award_id":"61673125","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4480269711","display_name":null,"funder_award_id":"2016A030310293","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4838502859","display_name":null,"funder_award_id":"2016A030310293","funder_id":"https://openalex.org/F4320321921","funder_display_name":"Natural Science Foundation of Guangdong Province"},{"id":"https://openalex.org/G5711791114","display_name":null,"funder_award_id":"2018YFB1308000","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5760752404","display_name":null,"funder_award_id":"Projects","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8028612691","display_name":null,"funder_award_id":"61603103","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8694528577","display_name":null,"funder_award_id":"2018YFB1308000","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321921","display_name":"Natural Science Foundation of Guangdong Province","ror":null},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3024906006.pdf","grobid_xml":"https://content.openalex.org/works/W3024906006.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1565402342","https://openalex.org/W1686810756","https://openalex.org/W1745334888","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W1923184257","https://openalex.org/W1923697677","https://openalex.org/W1969366022","https://openalex.org/W1985238052","https://openalex.org/W2066813062","https://openalex.org/W2090518410","https://openalex.org/W2097117768","https://openalex.org/W2098883970","https://openalex.org/W2124592697","https://openalex.org/W2168804568","https://openalex.org/W2194775991","https://openalex.org/W2395611524","https://openalex.org/W2397854647","https://openalex.org/W2412782625","https://openalex.org/W2475123968","https://openalex.org/W2485522583","https://openalex.org/W2560023338","https://openalex.org/W2560622558","https://openalex.org/W2563705555","https://openalex.org/W2592939477","https://openalex.org/W2630837129","https://openalex.org/W2753301142","https://openalex.org/W2775906317","https://openalex.org/W2799166040","https://openalex.org/W2809446072","https://openalex.org/W2884585870","https://openalex.org/W2886934227","https://openalex.org/W2910225133","https://openalex.org/W2910628332","https://openalex.org/W2912061451","https://openalex.org/W2915142517","https://openalex.org/W2940262938","https://openalex.org/W2963727650","https://openalex.org/W2963728677","https://openalex.org/W2963840672","https://openalex.org/W2963881378","https://openalex.org/W2964008506","https://openalex.org/W2964309882","https://openalex.org/W2980677578","https://openalex.org/W4293406525","https://openalex.org/W6637373629","https://openalex.org/W6640295612","https://openalex.org/W6666899075","https://openalex.org/W6696085341","https://openalex.org/W6717372056","https://openalex.org/W6739696289","https://openalex.org/W6744700018","https://openalex.org/W6748481559","https://openalex.org/W6753412334","https://openalex.org/W6761630670"],"related_works":["https://openalex.org/W2964954556","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4205800335","https://openalex.org/W2055202857","https://openalex.org/W2022929107","https://openalex.org/W80586315"],"abstract_inverted_index":{"Semantic":[0],"segmentation":[1,33,42,72,79,126,132],"is":[2,94,167,259],"one":[3],"of":[4,34,56,67,76,95,110,161,177,182,210,252,268],"the":[5,46,65,77,108,131,158,208,220,240,249,256,263],"most":[6,75],"fundamental":[7],"techniques":[8,43],"for":[9,17,40,98,143,186],"visual":[10],"intelligence,":[11],"which":[12,61,166,190],"plays":[13],"a":[14,121,136,180,230],"vital":[15],"role":[16],"indoor":[18,35,114,123,144,265],"service":[19,145],"robotic":[20],"tasks":[21],"such":[22],"as":[23,100,104],"scene":[24,124],"understanding,":[25],"autonomous":[26],"navigation":[27],"and":[28,51,59,70,84,134,140,153,213,222,243,271,273,282],"dexterous":[29],"manipulation.":[30],"However,":[31],"semantic":[32,78,125],"environments":[36],"poses":[37],"great":[38],"challenges":[39],"existing":[41],"due":[44],"to":[45,64,88,238],"complex":[47,83],"overlaps,":[48],"heavy":[49],"occlusions":[50],"cluttered":[52],"scenes":[53],"with":[54],"objects":[55],"different":[57],"shapes":[58],"scales,":[60],"may":[62],"lead":[63],"loss":[66],"edge":[68,188],"information":[69,185,217],"insufficient":[71],"accuracy.":[73],"And":[74],"networks":[80],"are":[81],"very":[82],"cannot":[85],"be":[86],"applied":[87],"mobile":[89],"robot":[90],"platforms.":[91],"Thus,":[92],"it":[93],"significant":[96],"importance":[97],"ensuring":[99],"few":[101],"network":[102,237],"parameters":[103],"possible":[105],"while":[106],"improving":[107],"detection":[109,189],"meaningful":[111],"edges":[112,133],"in":[113,196,199],"scenes.":[115],"In":[116],"this":[117],"paper,":[118],"we":[119,228],"present":[120,195],"novel":[122],"method":[127],"that":[128],"can":[129,206],"refine":[130],"achieve":[135],"balance":[137],"between":[138],"accuracy":[139],"model":[141],"complexity":[142],"robots.":[146],"Our":[147],"approach":[148,258],"systematically":[149],"incorporates":[150],"dilated":[151,204,241],"convolution":[152,205,242],"rich":[154,244],"convolutional":[155,245],"features":[156,246],"from":[157,248],"intermediate":[159,250],"layers":[160,198,251],"Convolutional":[162,234],"Neural":[163],"Networks":[164],"(CNN),":[165],"based":[168],"on":[169,262],"two":[170],"motivations:":[171],"(1)":[172],"The":[173,203],"middle":[174],"hidden":[175],"layer":[176],"CNN":[178],"contains":[179],"lot":[181],"potentially":[183],"useful":[184],"better":[187],"is,":[191],"however,":[192],"no":[193],"longer":[194],"latter":[197],"traditional":[200,253],"structures.":[201],"(2)":[202],"change":[207],"size":[209],"receptive":[211],"field":[212],"obtain":[214],"multi-scale":[215],"feature":[216],"without":[218],"losing":[219],"resolution":[221],"introducing":[223],"any":[224],"additional":[225],"parameters.":[226],"Thus":[227],"propose":[229],"new":[231],"end-to-end":[232],"Multi-Scale":[233],"Features":[235],"(MSCF)":[236],"integrate":[239],"extracted":[247],"CNN.":[254],"Finally,":[255],"resulting":[257],"extensively":[260],"evaluated":[261],"prestigious":[264],"image":[266],"datasets":[267],"SUN":[269],"RGB-D":[270],"NYUDv2,":[272],"shows":[274],"promising":[275],"improvements":[276],"over":[277],"state-of-the-art":[278],"baselines,":[279],"both":[280],"qualitatively":[281],"quantitatively.":[283]},"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":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}