{"id":"https://openalex.org/W2802487143","doi":"https://doi.org/10.1109/iscas.2018.8351736","title":"Using Deep Learning to Extract Scenery Information in Real Time Spatiotemporal Compressed Sensing","display_name":"Using Deep Learning to Extract Scenery Information in Real Time Spatiotemporal Compressed Sensing","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2802487143","doi":"https://doi.org/10.1109/iscas.2018.8351736","mag":"2802487143"},"language":"en","primary_location":{"id":"doi:10.1109/iscas.2018.8351736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2018.8351736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","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/A5112719601","display_name":"Xiao Wang","orcid":"https://orcid.org/0000-0002-0008-0659"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xiao Wang","raw_affiliation_strings":["Department of Computer Science, Boston University, Boston, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Boston University, Boston, MA, USA","institution_ids":["https://openalex.org/I111088046"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436609","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0001-5946-8319"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jie Zhang","raw_affiliation_strings":["Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101439585","display_name":"Tao Xiong","orcid":"https://orcid.org/0000-0003-1583-8669"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tao Xiong","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101413113","display_name":"Trac D. Tran","orcid":"https://orcid.org/0000-0002-0421-8416"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Trac Duy Tran","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103044811","display_name":"Sang Chin","orcid":"https://orcid.org/0000-0002-1913-4223"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sang Peter Chin","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037936459","display_name":"Ralph Etienne\u2010Cummings","orcid":"https://orcid.org/0000-0003-4445-973X"},"institutions":[{"id":"https://openalex.org/I145311948","display_name":"Johns Hopkins University","ror":"https://ror.org/00za53h95","country_code":"US","type":"education","lineage":["https://openalex.org/I145311948"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ralph Etienne-Cummings","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The Johns Hopkins University, Baltimore, MD, USA","institution_ids":["https://openalex.org/I145311948"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5112719601"],"corresponding_institution_ids":["https://openalex.org/I111088046"],"apc_list":null,"apc_paid":null,"fwci":0.8107,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.68872116,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"32","issue":null,"first_page":"1","last_page":"4"},"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/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11105","display_name":"Advanced Image Processing Techniques","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/mnist-database","display_name":"MNIST database","score":0.8180942535400391},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8115159273147583},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7810595035552979},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6294663548469543},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5625041723251343},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5479360818862915},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5479001998901367},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5022494792938232},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4886532127857208},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4686034917831421},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.43276768922805786}],"concepts":[{"id":"https://openalex.org/C190502265","wikidata":"https://www.wikidata.org/wiki/Q17069496","display_name":"MNIST database","level":3,"score":0.8180942535400391},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8115159273147583},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7810595035552979},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6294663548469543},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5625041723251343},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5479360818862915},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5479001998901367},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5022494792938232},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4886532127857208},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4686034917831421},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43276768922805786},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscas.2018.8351736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscas.2018.8351736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Symposium on Circuits and Systems (ISCAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1422049004","https://openalex.org/W1522301498","https://openalex.org/W2058742681","https://openalex.org/W2063978378","https://openalex.org/W2145096794","https://openalex.org/W2151364185","https://openalex.org/W2160547390","https://openalex.org/W2163605009","https://openalex.org/W2184344262","https://openalex.org/W2186665447","https://openalex.org/W2342293212","https://openalex.org/W2758329760","https://openalex.org/W2759718501","https://openalex.org/W2919115771","https://openalex.org/W2964121744","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W3036048022","https://openalex.org/W4309224979","https://openalex.org/W3026879719","https://openalex.org/W3013696689","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"One":[0],"of":[1,4,14],"the":[2,11,15,28,67,88,97,104,114,130],"problems":[3],"real":[5],"time":[6,119],"compressed":[7,68],"sensing":[8],"system":[9],"is":[10,19,117],"computational":[12,115],"cost":[13],"reconstruction":[16,134],"algorithms.":[17],"It":[18,76],"especially":[20],"problematic":[21],"for":[22,132],"close":[23],"loop":[24],"sensory":[25,29],"applications":[26],"where":[27],"parameters":[30],"needs":[31],"to":[32,36,38,110,136],"be":[33],"constantly":[34],"adjust":[35],"adapt":[37],"a":[39,43,71],"dynamic":[40],"scene.":[41],"Through":[42],"preliminary":[44],"experiment":[45],"with":[46],"MNIST":[47],"dataset,":[48],"we":[49,52],"showed":[50],"that":[51],"can":[53],"extract":[54],"some":[55],"scene":[56,60],"information":[57],"(object":[58],"recognition,":[59],"movement":[61],"direction":[62,95],"and":[63,90],"speed)":[64],"based":[65],"on":[66,123],"samples":[69],"using":[70,111],"deep":[72],"convolutional":[73],"neural":[74],"network.":[75],"achieves":[77],"100%":[78],"percent":[79],"accuracy":[80,106],"in":[81,86,92],"distinguishing":[82],"moving":[83,94],"velocity,":[84],"96.22%":[85],"recognizing":[87],"digit":[89],"90.04%":[91],"detecting":[93],"after":[96],"code":[98],"images":[99],"are":[100],"re-centered.":[101],"Even":[102],"though":[103],"classification":[105,122],"drops":[107],"slightly":[108],"compared":[109],"original":[112],"videos,":[113],"speed":[116],"two":[118],"faster":[120],"than":[121],"videos":[124],"directly.":[125],"This":[126],"method":[127],"also":[128],"eliminates":[129],"need":[131],"sparse":[133],"prior":[135],"classification.":[137]},"counts_by_year":[{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}