{"id":"https://openalex.org/W2510365547","doi":"https://doi.org/10.1109/icip.2016.7532689","title":"Recursive reduction net for large-scale high-dimensional data","display_name":"Recursive reduction net for large-scale high-dimensional data","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2510365547","doi":"https://doi.org/10.1109/icip.2016.7532689","mag":"2510365547"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532689","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 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/A5056791171","display_name":"Tsung-Wei Ke","orcid":"https://orcid.org/0000-0003-1315-3834"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tsung-Wei Ke","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5043386280","display_name":"Tyng-Luh Liu","orcid":"https://orcid.org/0000-0002-8366-5213"},"institutions":[{"id":"https://openalex.org/I4210098366","display_name":"Institute of Information Science, Academia Sinica","ror":"https://ror.org/00z83z196","country_code":"TW","type":"facility","lineage":["https://openalex.org/I4210098366","https://openalex.org/I84653119"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Tyng-Luh Liu","raw_affiliation_strings":["Academia Sinica, Institute of Information Science, Taiwan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Academia Sinica, Institute of Information Science, Taiwan","institution_ids":["https://openalex.org/I4210098366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210098366"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":null,"first_page":"1903","last_page":"1907"},"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":0.9991999864578247,"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":0.9991999864578247,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9979000091552734,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9970999956130981,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.8223509788513184},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.7046946287155151},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6551623940467834},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6196731328964233},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5333566665649414},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4856787919998169},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.45225241780281067},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3909875750541687},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36387842893600464},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2622900903224945},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07715147733688354}],"concepts":[{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.8223509788513184},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.7046946287155151},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6551623940467834},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6196731328964233},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5333566665649414},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4856787919998169},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.45225241780281067},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3909875750541687},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36387842893600464},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2622900903224945},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07715147733688354},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532689","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532689","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 Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6600000262260437,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1556531089","https://openalex.org/W1975900269","https://openalex.org/W2012592962","https://openalex.org/W2100495367","https://openalex.org/W2103924867","https://openalex.org/W2108598243","https://openalex.org/W2108665656","https://openalex.org/W2116064496","https://openalex.org/W2145094598","https://openalex.org/W2152424459","https://openalex.org/W2154872931","https://openalex.org/W2162064258","https://openalex.org/W2997574889","https://openalex.org/W6676297131","https://openalex.org/W6681096077","https://openalex.org/W6682359208"],"related_works":["https://openalex.org/W4234886518","https://openalex.org/W2389591058","https://openalex.org/W2382112581","https://openalex.org/W3124036233","https://openalex.org/W4229787472","https://openalex.org/W3176621072","https://openalex.org/W2486541857","https://openalex.org/W2108840191","https://openalex.org/W2759366996","https://openalex.org/W2110679372"],"abstract_inverted_index":{"Performing":[0],"dimensionality":[1,51],"reduction":[2,45,52,69,85],"on":[3,110],"features":[4],"is":[5,61],"essential":[6],"in":[7],"tackling":[8],"a":[9,84,88,120],"majority":[10],"of":[11,21,96,102],"large-scale":[12,54],"computer":[13],"vision":[14],"and":[15,87,105],"pattern":[16],"recognition":[17],"problems.":[18],"The":[19,57],"popularity":[20],"adopting":[22],"high-dimensional":[23,55],"descriptors":[24],"has":[25],"caused":[26],"conventional":[27],"techniques":[28],"such":[29],"as":[30,43,78],"PCA":[31,77],"inefficient":[32],"or":[33],"even":[34],"unfeasible.":[35],"We":[36],"introduce":[37],"an":[38],"unsupervised":[39],"deep-net":[40],"approach,":[41],"termed":[42],"recursive":[44],"net":[46,86],"(RRN),":[47],"to":[48,63,66,82],"carrying":[49],"out":[50,107],"for":[53],"data.":[56],"proposed":[58],"iterative":[59],"algorithm":[60],"designed":[62],"learn":[64],"how":[65],"merge":[67],"piecewise":[68],"results":[70],"effectively.":[71],"To":[72,92],"this":[73],"end,":[74],"we":[75,98],"use":[76],"the":[79,94,100],"teacher":[80],"model":[81],"establish":[83],"fusion":[89],"net,":[90],"respectively.":[91],"demonstrate":[93],"usefulness":[95],"RRN,":[97],"evaluate":[99],"property":[101],"variance":[103],"explaining":[104],"carry":[106],"extensive":[108],"experiments":[109],"similarity":[111],"search":[112],"via":[113],"binary":[114],"coding,":[115],"which":[116],"would":[117],"benefit":[118],"from":[119],"proper":[121],"dimensionality-reduction":[122],"scheme.":[123]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}