{"id":"https://openalex.org/W3091682113","doi":"https://doi.org/10.1109/icip40778.2020.9191033","title":"Cascaded Context Dependency: An Extremely Lightweight Module For Deep Convolutional Neural Networks","display_name":"Cascaded Context Dependency: An Extremely Lightweight Module For Deep Convolutional Neural Networks","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3091682113","doi":"https://doi.org/10.1109/icip40778.2020.9191033","mag":"3091682113"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-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/A5100701885","display_name":"Xu Ma","orcid":"https://orcid.org/0000-0002-5794-119X"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xu Ma","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033267613","display_name":"Zhinan Qiao","orcid":"https://orcid.org/0000-0002-8103-3829"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhinan Qiao","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040789505","display_name":"Jingda Guo","orcid":"https://orcid.org/0000-0002-6967-0024"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingda Guo","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103954876","display_name":"Sihai Tang","orcid":"https://orcid.org/0000-0002-2438-4163"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sihai Tang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101981863","display_name":"Qi Chen","orcid":"https://orcid.org/0000-0001-5195-8516"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qi Chen","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006400453","display_name":"Qing Yang","orcid":"https://orcid.org/0000-0003-2744-9556"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qing Yang","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5082758762","display_name":"Song Fu","orcid":"https://orcid.org/0000-0002-7705-0829"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Fu","raw_affiliation_strings":["Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of North Texas, Denton, Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100701885"],"corresponding_institution_ids":["https://openalex.org/I123534392"],"apc_list":null,"apc_paid":null,"fwci":0.0977,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.40759226,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":null,"issue":null,"first_page":"1741","last_page":"1745"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8053940534591675},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6268677115440369},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.619853138923645},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6074082851409912},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5745206475257874},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5613867044448853},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5159193277359009},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.4906448423862457},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4643810987472534},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43710675835609436},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3964560627937317},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3862811028957367},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.1402263045310974},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07771125435829163}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8053940534591675},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6268677115440369},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.619853138923645},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6074082851409912},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5745206475257874},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5613867044448853},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5159193277359009},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.4906448423862457},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4643810987472534},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43710675835609436},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3964560627937317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3862811028957367},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.1402263045310974},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07771125435829163},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","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},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191033","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191033","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W2097117768","https://openalex.org/W2109255472","https://openalex.org/W2117539524","https://openalex.org/W2194775991","https://openalex.org/W2490270993","https://openalex.org/W2502312327","https://openalex.org/W2549139847","https://openalex.org/W2565639579","https://openalex.org/W2884585870","https://openalex.org/W2898732869","https://openalex.org/W2899771611","https://openalex.org/W2903226808","https://openalex.org/W2922509574","https://openalex.org/W2945164022","https://openalex.org/W2949117887","https://openalex.org/W2963091558","https://openalex.org/W2963351448","https://openalex.org/W2963403868","https://openalex.org/W2963420686","https://openalex.org/W2963984455","https://openalex.org/W2964151039","https://openalex.org/W2964241181","https://openalex.org/W2981408784","https://openalex.org/W2981413347","https://openalex.org/W2982220924","https://openalex.org/W2983446232","https://openalex.org/W2997890315","https://openalex.org/W4385245566","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6678174250","https://openalex.org/W6722946945","https://openalex.org/W6724804524","https://openalex.org/W6739901393","https://openalex.org/W6743731764","https://openalex.org/W6749954789","https://openalex.org/W6753412334","https://openalex.org/W6756040250","https://openalex.org/W6757040593","https://openalex.org/W6761855798","https://openalex.org/W6780226713"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2067317451","https://openalex.org/W2154771632","https://openalex.org/W4211085505","https://openalex.org/W4249847449","https://openalex.org/W3122478268","https://openalex.org/W2084758217","https://openalex.org/W44395729","https://openalex.org/W408804804","https://openalex.org/W4231021675"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,47,133],"present":[4],"a":[5,12,64],"cascaded":[6,76],"context":[7,41],"dependency":[8,42,71],"module,":[9],"which":[10],"is":[11],"highly":[13],"lightweight":[14],"module":[15,96],"that":[16,118],"can":[17,97,121],"improve":[18,107],"the":[19,32,40,51,59,70,108,164,169,191],"performance":[20],"of":[21,53],"deep":[22],"convolutional":[23],"neural":[24],"networks":[25],"for":[26,78,168],"various":[27],"visual":[28],"tasks.":[29],"Inspired":[30],"by":[31],"feature":[33,55,79],"pyramid":[34],"work":[35,43],"in":[36,44,63],"object":[37,170],"detection":[38,171],"and":[39,61,75,92,113,175,195],"image":[45],"recognition,":[46],"consider":[48],"to":[49,57,106,199],"cascade":[50],"contexts":[52,77],"multiscale":[54],"maps":[56],"aggregate":[58],"locality":[60],"globality":[62],"local":[65],"region.":[66],"We":[67,188],"further":[68],"extract":[69],"between":[72],"original":[73],"input":[74],"recalibration.":[80],"Without":[81],"employing":[82],"learnable":[83],"layers,":[84],"our":[85,119,158],"method":[86,120,159],"introduces":[87],"almost":[88],"no":[89],"additional":[90],"parameters":[91],"computations.":[93],"Furthermore,":[94],"Our":[95],"be":[98],"seamlessly":[99],"plugged":[100],"into":[101],"many":[102],"existing":[103],"CNN":[104],"architectures":[105],"performance.":[109],"Experiments":[110],"on":[111,124,146,148,163],"ImageNet":[112,149],"MS":[114,165],"COCO":[115,166],"benchmarks":[116],"indicate":[117],"achieve":[122,134],"results":[123],"par":[125],"with":[126,153],"or":[127],"better":[128],"than":[129],"related":[130],"work.":[131],"Qualitatively,":[132],"an":[135],"absolute":[136],"1.42%":[137],"(77.3137%":[138],"vs.":[139],"75.8974%)":[140],"top-1":[141],"classification":[142],"accuracy":[143],"improvement":[144],"based":[145],"ResNet50":[147],"2012":[150],"validation":[151],"set":[152],"negligible":[154],"computational":[155],"overhead.":[156],"Besides,":[157],"yields":[160],"significant":[161],"gains":[162],"benchmark":[167],"task.":[172],"All":[173],"codes":[174],"models":[176],"are":[177],"made":[178],"publicly":[179],"available":[180],"<sup":[181,185],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[182,186],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[183,187],".":[184],"submit":[189],"all":[190],"codes,":[192],"pre-trained":[193],"models,":[194],"training":[196],"log":[197],"files":[198],"https://github.com/13952522076/ParameterFree.":[200]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}