{"id":"https://openalex.org/W2406876511","doi":"https://doi.org/10.1109/icassp.2016.7471890","title":"Learning discriminative and shareable patches for scene classification","display_name":"Learning discriminative and shareable patches for scene classification","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2406876511","doi":"https://doi.org/10.1109/icassp.2016.7471890","mag":"2406876511"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7471890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5087200239","display_name":"Shoucheng Ni","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shoucheng Ni","raw_affiliation_strings":["Institue of Image Communication and Network Engineering, Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Network Engineering, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026216171","display_name":"Qieshi Zhangg","orcid":null},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Qieshi Zhangg","raw_affiliation_strings":["Waseda Daigaku, Shinjuku-ku, Tokyo, JP"],"affiliations":[{"raw_affiliation_string":"Waseda Daigaku, Shinjuku-ku, Tokyo, JP","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066452160","display_name":"Sei\u2010ichiro Kamata","orcid":"https://orcid.org/0000-0002-1496-2417"},"institutions":[{"id":"https://openalex.org/I150744194","display_name":"Waseda University","ror":"https://ror.org/00ntfnx83","country_code":"JP","type":"education","lineage":["https://openalex.org/I150744194"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sei-ichiro Kamata","raw_affiliation_strings":["Production and Systems, Waseda University"],"affiliations":[{"raw_affiliation_string":"Production and Systems, Waseda University","institution_ids":["https://openalex.org/I150744194"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023787090","display_name":"Chongyang Zhang","orcid":"https://orcid.org/0000-0001-7292-0445"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chongyang Zhang","raw_affiliation_strings":["Institue of Image Communication and Network Engineering, Shanghai Jiao Tong University"],"affiliations":[{"raw_affiliation_string":"Institue of Image Communication and Network Engineering, Shanghai Jiao Tong University","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5087200239"],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":0.501,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.71364559,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"abs 1409 1556","issue":null,"first_page":"1317","last_page":"1321"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8964782953262329},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.777618944644928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7556235790252686},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6510134339332581},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6169626116752625},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6152876615524292},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6148256659507751},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5666534900665283},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5656272768974304},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.538270115852356},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5078869462013245},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.42979228496551514},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4245268702507019},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19349482655525208},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06297731399536133}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8964782953262329},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.777618944644928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7556235790252686},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6510134339332581},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6169626116752625},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6152876615524292},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6148256659507751},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5666534900665283},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5656272768974304},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.538270115852356},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5078869462013245},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.42979228496551514},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4245268702507019},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19349482655525208},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06297731399536133},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7471890","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7471890","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W280294731","https://openalex.org/W315880484","https://openalex.org/W1590510366","https://openalex.org/W1686810756","https://openalex.org/W1976921161","https://openalex.org/W1999478155","https://openalex.org/W2001531180","https://openalex.org/W2033832873","https://openalex.org/W2062118960","https://openalex.org/W2070792803","https://openalex.org/W2112274848","https://openalex.org/W2115628259","https://openalex.org/W2119853387","https://openalex.org/W2137680370","https://openalex.org/W2139468722","https://openalex.org/W2152161678","https://openalex.org/W2155541015","https://openalex.org/W2161969291","https://openalex.org/W2162915993","https://openalex.org/W2407615025","https://openalex.org/W2962835968","https://openalex.org/W4294375521","https://openalex.org/W6610111499","https://openalex.org/W6610784610","https://openalex.org/W6637373629","https://openalex.org/W6676759488","https://openalex.org/W6677322961","https://openalex.org/W6678144016"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W3119773509","https://openalex.org/W3208297503","https://openalex.org/W2889153461","https://openalex.org/W2964117661","https://openalex.org/W4388405611","https://openalex.org/W2619127353"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,61,91],"problem":[4],"of":[5,20,51,64,82,118],"scene":[6,114],"classification":[7],"and":[8,12,23,37,44,56],"proposes":[9],"learning":[10,21],"discriminative":[11,22],"shareable":[13,24],"patches":[14,25,29,65],"(LDSP)":[15],"method.":[16],"The":[17,104],"main":[18],"idea":[19],"is":[26,54,88,102],"to":[27,58,71],"discover":[28],"that":[30],"exhibit":[31],"both":[32],"large":[33,38],"between-class":[34],"dissimilarity":[35],"(discriminative)":[36],"within-class":[39],"similarity":[40,63],"(shareable).":[41],"A":[42],"novel":[43],"efficient":[45],"re-clustering,":[46],"based":[47],"on":[48,111],"co-occurrence":[49],"relationship":[50],"first-step":[52],"clustering,":[53],"proposed":[55],"conducted":[57],"further":[59],"enhance":[60],"visual":[62],"within":[66],"each":[67],"cluster.":[68],"In":[69,90],"order":[70],"establish":[72],"appropriate":[73],"criteria":[74],"for":[75],"selecting":[76],"desired":[77],"patches,":[78],"a":[79,93],"condensed":[80],"representation":[81],"image":[83],"features":[84],"called":[85],"feature":[86,95],"epitome":[87],"introduced.":[89],"classification,":[92],"patch":[94],"involving":[96],"pre-trained":[97],"convolutional":[98],"neural":[99],"network":[100],"model":[101],"investigated.":[103],"experimental":[105],"result":[106],"outperforms":[107],"existing":[108],"single-feature":[109],"methods":[110],"MIT":[112],"67":[113],"benchmark":[115],"in":[116],"term":[117],"mean":[119],"Accuracy":[120],"Precision.":[121]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}