{"id":"https://openalex.org/W3160965271","doi":"https://doi.org/10.1109/icpr48806.2021.9412503","title":"Context-Aware Residual Module for Image Classification","display_name":"Context-Aware Residual Module for Image Classification","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3160965271","doi":"https://doi.org/10.1109/icpr48806.2021.9412503","mag":"3160965271"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5006792341","display_name":"Jing Bai","orcid":"https://orcid.org/0000-0003-4247-6210"},"institutions":[{"id":"https://openalex.org/I21642278","display_name":"Ningxia University","ror":"https://ror.org/04j7b2v61","country_code":"CN","type":"education","lineage":["https://openalex.org/I21642278"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jing Bai","raw_affiliation_strings":["Ningxia Province Key Laboratory of Intelligent Information and Data Processing, Yinchuan, China"],"affiliations":[{"raw_affiliation_string":"Ningxia Province Key Laboratory of Intelligent Information and Data Processing, Yinchuan, China","institution_ids":["https://openalex.org/I21642278"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400800","display_name":"Ran Chen","orcid":"https://orcid.org/0000-0002-2770-4070"},"institutions":[{"id":"https://openalex.org/I3019309368","display_name":"North Minzu University","ror":"https://ror.org/05xjevr11","country_code":"CN","type":"education","lineage":["https://openalex.org/I3019309368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran Chen","raw_affiliation_strings":["School of Computer Science and Engineering, North Minzu University, Yinchuan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, North Minzu University, Yinchuan, China","institution_ids":["https://openalex.org/I3019309368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006792341"],"corresponding_institution_ids":["https://openalex.org/I21642278"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04593137,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3388","last_page":"3395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994000196456909,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9983000159263611,"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":0.8256587982177734},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.6822746396064758},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6706139445304871},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6363709568977356},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6152655482292175},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.560640275478363},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5555885434150696},{"id":"https://openalex.org/keywords/spatial-contextual-awareness","display_name":"Spatial contextual awareness","score":0.5256922245025635},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5248432159423828},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4818619191646576},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46653443574905396},{"id":"https://openalex.org/keywords/residual-neural-network","display_name":"Residual neural network","score":0.4469006061553955},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4320999085903168},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3739684820175171},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3738425672054291},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07653039693832397}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8256587982177734},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.6822746396064758},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6706139445304871},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6363709568977356},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6152655482292175},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.560640275478363},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5555885434150696},{"id":"https://openalex.org/C64754055","wikidata":"https://www.wikidata.org/wiki/Q7574053","display_name":"Spatial contextual awareness","level":2,"score":0.5256922245025635},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5248432159423828},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4818619191646576},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46653443574905396},{"id":"https://openalex.org/C2944601119","wikidata":"https://www.wikidata.org/wiki/Q43744058","display_name":"Residual neural network","level":3,"score":0.4469006061553955},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4320999085903168},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3739684820175171},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3738425672054291},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07653039693832397},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3091883112","display_name":null,"funder_award_id":"61762003","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2097117768","https://openalex.org/W2108598243","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2279098554","https://openalex.org/W2401231614","https://openalex.org/W2531409750","https://openalex.org/W2549139847","https://openalex.org/W2560023338","https://openalex.org/W2612445135","https://openalex.org/W2752782242","https://openalex.org/W2823177849","https://openalex.org/W2884585870","https://openalex.org/W2895598217","https://openalex.org/W2916798096","https://openalex.org/W2928165649","https://openalex.org/W2941030194","https://openalex.org/W2959203930","https://openalex.org/W2962858109","https://openalex.org/W2962971773","https://openalex.org/W2963241429","https://openalex.org/W2963420686","https://openalex.org/W2963446712","https://openalex.org/W2963495494","https://openalex.org/W2964137095","https://openalex.org/W2988396473","https://openalex.org/W3023803297","https://openalex.org/W3118608800","https://openalex.org/W4297775537","https://openalex.org/W6674914833","https://openalex.org/W6684191040","https://openalex.org/W6753261499","https://openalex.org/W6753412334","https://openalex.org/W6755102754","https://openalex.org/W6787972765"],"related_works":["https://openalex.org/W3196952692","https://openalex.org/W2984708981","https://openalex.org/W4300939921","https://openalex.org/W2972212393","https://openalex.org/W4383097772","https://openalex.org/W2964350391","https://openalex.org/W2274287116","https://openalex.org/W2897517148","https://openalex.org/W2967403871","https://openalex.org/W2983358626"],"abstract_inverted_index":{"Attention":[0],"module":[1,81,98,123],"has":[2,38],"achieved":[3],"great":[4],"success":[5],"in":[6,43,56,87],"numerous":[7],"vision":[8],"tasks.":[9],"However,":[10,49],"existing":[11],"visual":[12,108],"attention":[13,97],"modules":[14,137,177],"generally":[15],"consider":[16],"the":[17,33,50,75,107,135,155,187],"features":[18,52,109],"of":[19,27,47,92,110,134,190],"a":[20,44,57,70,78,93,119,149,180],"single-scale,":[21],"and":[22,114,118,170,186,192],"cannot":[23],"make":[24],"full":[25],"use":[26],"their":[28,66],"multi-scale":[29,34,51,95,120],"contextual":[30,67],"information.":[31,130],"Meanwhile,":[32],"spatial":[35,121,129],"feature":[36],"representation":[37],"demonstrated":[39],"its":[40,111,115],"outstanding":[41],"performance":[42],"wide":[45],"range":[46],"applications.":[48],"are":[53],"always":[54],"represented":[55],"layer-wise":[58],"manner,":[59],"i.e.":[60],"it":[61],"is":[62,85],"impossible":[63],"to":[64,100,125,153],"know":[65],"information":[68],"at":[69],"granular":[71],"level.":[72],"Focusing":[73],"on":[74,161],"above":[76],"issue,":[77],"context-aware":[79,156],"residual":[80,151],"for":[82],"image":[83,145,163],"classification":[84,146],"proposed":[86,176],"this":[88],"paper.":[89],"It":[90],"consists":[91],"novel":[94],"channel":[96,103],"MSCAM":[99],"learn":[101],"refined":[102],"weights":[104],"by":[105],"considering":[106],"own":[112],"scale":[113],"surrounding":[116],"fields,":[117],"aware":[122],"MSSAM":[124],"further":[126],"capture":[127],"more":[128],"Either":[131],"or":[132],"both":[133],"two":[136],"can":[138],"be":[139],"plugged":[140],"into":[141],"any":[142],"CNN-based":[143],"backbone":[144],"architecture":[147],"with":[148],"short":[150],"connection":[152],"obtain":[154],"enhanced":[157],"features.":[158],"The":[159],"experiments":[160],"public":[162],"recognition":[164],"datasets":[165],"including":[166],"CIFAR10,":[167],"CIFAR100,":[168],"Tiny-ImageNet":[169],"ImageNet":[171],"consistently":[172],"demonstrate":[173],"that":[174],"our":[175],"significantly":[178],"outperforms":[179],"wide-used":[181],"state-of-the-art":[182],"methods,":[183],"e.g.,":[184],"ResNet":[185],"lightweight":[188],"networks":[189],"MobileNet":[191],"SqueezeeNet.":[193]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
