{"id":"https://openalex.org/W2794279536","doi":"https://doi.org/10.1109/robio.2017.8324821","title":"Learning object recognition based on compressive sampling","display_name":"Learning object recognition based on compressive sampling","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2794279536","doi":"https://doi.org/10.1109/robio.2017.8324821","mag":"2794279536"},"language":"en","primary_location":{"id":"doi:10.1109/robio.2017.8324821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2017.8324821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","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/A5011675206","display_name":"Congjian Li","orcid":null},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Congjian Li","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101653972","display_name":"Yu Cheng","orcid":"https://orcid.org/0000-0002-8686-4277"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yu Cheng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Hong Kong, East Lansing, MI, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Hong Kong, East Lansing, MI, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012480129","display_name":"Sheng Bi","orcid":"https://orcid.org/0000-0001-8292-2110"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sheng Bi","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057276700","display_name":"Yingfeng Cai","orcid":"https://orcid.org/0000-0002-0633-9887"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfeng Cai","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023212284","display_name":"Ning Xi","orcid":"https://orcid.org/0000-0001-8276-5696"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Ning Xi","raw_affiliation_strings":["Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5011675206"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.4802,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.6543317,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2663","last_page":"2668"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9901999831199646,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9872999787330627,"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/computer-science","display_name":"Computer science","score":0.8083333373069763},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7965962886810303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7504607439041138},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6819868087768555},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6525601744651794},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5957132577896118},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.581835925579071},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5696343183517456},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5254023671150208},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4804643988609314},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.47573092579841614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41717618703842163},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41225308179855347}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8083333373069763},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7965962886810303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7504607439041138},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6819868087768555},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6525601744651794},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5957132577896118},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.581835925579071},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5696343183517456},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5254023671150208},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4804643988609314},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.47573092579841614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41717618703842163},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41225308179855347},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robio.2017.8324821","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robio.2017.8324821","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Robotics and Biomimetics (ROBIO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.47999998927116394,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W6838700","https://openalex.org/W1956120499","https://openalex.org/W1965875863","https://openalex.org/W2103560185","https://openalex.org/W2115579991","https://openalex.org/W2119667497","https://openalex.org/W2125680629","https://openalex.org/W2127271355","https://openalex.org/W2129812935","https://openalex.org/W2130120519","https://openalex.org/W2153635508","https://openalex.org/W2163922914","https://openalex.org/W2273561594","https://openalex.org/W2343568200","https://openalex.org/W2537979761","https://openalex.org/W2735049927","https://openalex.org/W2751850814","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2896778670","https://openalex.org/W2114428029"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"an":[5],"object":[6],"recognition":[7,62,110],"algorithm":[8],"allowing":[9],"for":[10,80],"learning":[11],"in":[12,28],"the":[13,19,35,48,61,75,81,87,103,114],"compressed":[14,52],"space":[15,21],"and":[16,64,112],"reconstructing":[17],"to":[18,25,45,51,74],"spatial":[20,30],"when":[22],"images":[23,53],"need":[24],"be":[26],"processed":[27],"their":[29],"forms.":[31],"Instead":[32],"of":[33,89],"using":[34],"traditional":[36],"cameras,":[37],"a":[38,68,72,93,108],"novel":[39],"compressive":[40,56],"sampling":[41,57],"camera":[42],"is":[43,99],"simulated":[44],"directly":[46],"capture":[47],"natural":[49],"scene":[50],"based":[54],"on":[55,67,92],"theory.":[58],"We":[59,84],"evaluate":[60],"performance":[63],"reconstruction":[65],"quality":[66],"traffic":[69],"database":[70],"providing":[71],"solution":[73],"reliable":[76],"situation":[77],"awareness":[78],"problem":[79],"self-driving":[82],"cars.":[83],"also":[85],"exploit":[86],"effectiveness":[88],"our":[90],"method":[91],"publicly":[94],"available":[95],"face":[96],"database.":[97],"It":[98],"experimentally":[100],"observed":[101],"that":[102],"proposed":[104],"approach":[105],"can":[106],"obtain":[107],"high":[109],"rate":[111],"achieve":[113],"image":[115],"reconstruction.":[116]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}