{"id":"https://openalex.org/W3007575627","doi":"https://doi.org/10.1145/3373087.3375358","title":"CANSEE: Customized Accelerator for Neural Signal Enhancement and Extraction from the Calcium Image in Real Time","display_name":"CANSEE: Customized Accelerator for Neural Signal Enhancement and Extraction from the Calcium Image in Real Time","publication_year":2020,"publication_date":"2020-02-23","ids":{"openalex":"https://openalex.org/W3007575627","doi":"https://doi.org/10.1145/3373087.3375358","mag":"3007575627"},"language":"en","primary_location":{"id":"doi:10.1145/3373087.3375358","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373087.3375358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","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/A5002478369","display_name":"Zhe Chen","orcid":"https://orcid.org/0000-0002-5371-2058"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Zhe Chen","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011271205","display_name":"Garrett J. Blair","orcid":"https://orcid.org/0000-0003-2724-8914"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Garrett Blair","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061050227","display_name":"Hugh T. Blair","orcid":"https://orcid.org/0000-0001-8256-5109"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hugh T. Blair","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016776689","display_name":"Jason Cong","orcid":"https://orcid.org/0000-0003-2887-6963"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jason Cong","raw_affiliation_strings":["University of California, Los Angeles, Los Angeles, CA, USA"],"affiliations":[{"raw_affiliation_string":"University of California, Los Angeles, Los Angeles, CA, USA","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5002478369"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.01271955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"318","last_page":"318"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9994000196456909,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9983999729156494,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7489516735076904},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.6027461290359497},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.561659574508667},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5596802234649658},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5340005159378052},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.49204084277153015},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.4859100878238678},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.4138646125793457},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.41348502039909363},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.3386967182159424},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3384931683540344},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.2631251811981201},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.22699910402297974},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.14456570148468018},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.07640820741653442}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7489516735076904},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.6027461290359497},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.561659574508667},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5596802234649658},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5340005159378052},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.49204084277153015},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.4859100878238678},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.4138646125793457},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.41348502039909363},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.3386967182159424},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3384931683540344},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.2631251811981201},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.22699910402297974},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.14456570148468018},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.07640820741653442},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3373087.3375358","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3373087.3375358","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.8999999761581421,"id":"https://metadata.un.org/sdg/7"}],"awards":[{"id":"https://openalex.org/G7143216947","display_name":null,"funder_award_id":"DBI-1707408","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2891987081","https://openalex.org/W4210376836","https://openalex.org/W4210925376","https://openalex.org/W1633995705","https://openalex.org/W2596211269","https://openalex.org/W2360384790","https://openalex.org/W4232397253","https://openalex.org/W4235913033","https://openalex.org/W2109284253","https://openalex.org/W2039966832"],"abstract_inverted_index":{"Miniaturized":[0],"fluorescent":[1],"calcium":[2,24,71,84],"imaging":[3],"miniscope":[4],"has":[5],"become":[6],"a":[7,15,61,125],"prominent":[8],"technique":[9],"in":[10,20,73,141],"monitoring":[11],"the":[12,43,59,80,83,88,105,114,122,146,149],"activity":[13],"of":[14,18,138],"large":[16],"population":[17],"neurons":[19],"vivo.":[21],"However,":[22],"existing":[23],"image":[25,72,85],"processing":[26,45,100],"algorithms":[27],"are":[28,39],"developed":[29],"for":[30,51,64],"off-line":[31],"analysis,":[32],"and":[33,68,87,134],"their":[34],"implementations":[35],"on":[36,113,124,148],"general-purpose":[37],"processors":[38],"difficult":[40],"to":[41,93,145],"meet":[42],"real-time":[44],"requirement":[46],"under":[47],"constrained":[48],"energy":[49,142],"budget":[50],"closed-loop":[52],"applications.":[53],"In":[54],"this":[55],"paper,":[56],"we":[57],"propose":[58],"CANSEE,":[60],"customized":[62],"accelerator":[63,77,123],"neural":[65],"signal":[66],"enhancement":[67],"extraction":[69],"from":[70,91],"real":[74],"time.":[75],"The":[76,129],"can":[78,108],"perform":[79],"motion":[81],"correction,":[82],"enhancement,":[86],"fluorescence":[89],"tracing":[90],"up":[92],"512":[94],"cells":[95,111],"with":[96],"less":[97],"than":[98],"1-ms":[99],"latency.":[101],"We":[102,120],"also":[103],"designed":[104],"hardware":[106],"that":[107],"detect":[109],"new":[110],"based":[112],"long":[115],"short-term":[116],"memory":[117],"(LSTM)":[118],"inference.":[119],"implemented":[121],"Xilinx":[126],"Ultra96":[127],"FPGA.":[128],"implementation":[130],"achieves":[131],"15.8x":[132],"speedup":[133],"over":[135],"2":[136],"orders":[137],"magnitude":[139],"improvement":[140],"efficiency":[143],"compared":[144],"evaluation":[147],"multi-core":[150],"CPU.":[151]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
