{"id":"https://openalex.org/W2295119554","doi":"https://doi.org/10.1109/icip.2015.7350829","title":"Randomized spatial pooling in deep convolutional networks for scene recognition","display_name":"Randomized spatial pooling in deep convolutional networks for scene recognition","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2295119554","doi":"https://doi.org/10.1109/icip.2015.7350829","mag":"2295119554"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7350829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5113960258","display_name":"Mu Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mu Yang","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University","Megvii Inc., Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Megvii Inc., Beijing, P. R. China","institution_ids":["https://openalex.org/I4401726805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101800886","display_name":"Brian Li","orcid":"https://orcid.org/0000-0002-7496-9506"},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Brian Li","raw_affiliation_strings":["Megvii Inc., Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Megvii Inc., Beijing, P. R. China","institution_ids":["https://openalex.org/I4401726805"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080414420","display_name":"Haoqiang Fan","orcid":"https://orcid.org/0000-0002-7398-6873"},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqiang Fan","raw_affiliation_strings":["Department of Computer Science and Technology, Tsinghua University","Megvii Inc., Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tsinghua University","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Megvii Inc., Beijing, P. R. China","institution_ids":["https://openalex.org/I4401726805"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101909495","display_name":"Yuning Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I4401726805","display_name":"Megvii (China)","ror":"https://ror.org/040b32p69","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726805"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuning Jiang","raw_affiliation_strings":["Megvii Inc., Beijing, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Megvii Inc., Beijing, P. R. China","institution_ids":["https://openalex.org/I4401726805"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"402","last_page":"406"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9969000220298767,"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/pooling","display_name":"Pooling","score":0.949732780456543},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7971546649932861},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7382175922393799},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6975067257881165},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6140265464782715},{"id":"https://openalex.org/keywords/spatial-analysis","display_name":"Spatial analysis","score":0.5020694732666016},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4989662170410156},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4809795618057251},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4387091100215912},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4349942207336426},{"id":"https://openalex.org/keywords/partition","display_name":"Partition (number theory)","score":0.41392314434051514},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3514971137046814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09014415740966797},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0594639778137207},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.05510440468788147}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.949732780456543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7971546649932861},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7382175922393799},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6975067257881165},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6140265464782715},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.5020694732666016},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4989662170410156},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4809795618057251},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4387091100215912},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4349942207336426},{"id":"https://openalex.org/C42812","wikidata":"https://www.wikidata.org/wiki/Q1082910","display_name":"Partition (number theory)","level":2,"score":0.41392314434051514},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3514971137046814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09014415740966797},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0594639778137207},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.05510440468788147},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/icip.2015.7350829","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350829","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.6600000262260437}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1487583988","https://openalex.org/W1566135517","https://openalex.org/W1991031523","https://openalex.org/W2033832873","https://openalex.org/W2062118960","https://openalex.org/W2107034620","https://openalex.org/W2113740552","https://openalex.org/W2113855951","https://openalex.org/W2115628259","https://openalex.org/W2134670479","https://openalex.org/W2139468722","https://openalex.org/W2151103935","https://openalex.org/W2152161678","https://openalex.org/W2155893237","https://openalex.org/W2162915993","https://openalex.org/W2163605009","https://openalex.org/W2950094539","https://openalex.org/W2963542991","https://openalex.org/W4250737575","https://openalex.org/W7075742223"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W147410782","https://openalex.org/W4401096132","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3133861977","https://openalex.org/W2951211570","https://openalex.org/W3103566983","https://openalex.org/W3029198973"],"abstract_inverted_index":{"The":[0,93],"spatial":[1,13,39,48],"layout":[2,14,49],"of":[3,104],"scene":[4,27,98],"images":[5],"is":[6,43,79],"essential":[7],"to":[8,45,69,81,88],"recognizing":[9],"them.":[10],"Without":[11],"considering":[12],"information,":[15],"the":[16,37,47,52,57,63,67,84,90,97,102,105],"deep":[17,53],"convolutional":[18],"neural":[19],"networks":[20],"could":[21],"not":[22],"achieve":[23],"satisfied":[24],"performance":[25],"on":[26,96],"recognition.":[28],"In":[29],"this":[30],"paper":[31],"a":[32,75],"novel":[33],"network":[34],"architecture,":[35],"namely":[36],"randomized":[38,61],"pooling":[40],"(RS-Pooling)":[41],"layer,":[42],"proposed":[44,106],"incorporate":[46],"information":[50],"into":[51],"model.":[54],"By":[55],"partitioning":[56],"feature":[58],"maps":[59],"via":[60],"patterns,":[62],"RS-Pooling":[64,107],"layer":[65],"offers":[66],"probability":[68],"handle":[70],"various":[71],"image":[72,91],"layouts.":[73],"Moreover,":[74],"maxout":[76],"objective":[77],"function":[78],"adopted":[80],"adaptively":[82],"choose":[83],"optimal":[85],"partition":[86],"pattern":[87],"characterize":[89],"layout.":[92],"experimental":[94],"results":[95],"recognition":[99],"benchmarks":[100],"demonstrate":[101],"effectiveness":[103],"architecture.":[108]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}