{"id":"https://openalex.org/W3127332605","doi":"https://doi.org/10.1109/icta50426.2020.9331957","title":"A Fast and Efficient FPGA-based Level Set Hardware Accelerator for Image Segmentation","display_name":"A Fast and Efficient FPGA-based Level Set Hardware Accelerator for Image Segmentation","publication_year":2020,"publication_date":"2020-11-23","ids":{"openalex":"https://openalex.org/W3127332605","doi":"https://doi.org/10.1109/icta50426.2020.9331957","mag":"3127332605"},"language":"en","primary_location":{"id":"doi:10.1109/icta50426.2020.9331957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icta50426.2020.9331957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)","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/A5100346548","display_name":"Ye Liu","orcid":"https://orcid.org/0000-0002-2686-3002"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ye Liu","raw_affiliation_strings":["School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100654259","display_name":"Yin Wang","orcid":"https://orcid.org/0000-0002-8671-9571"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yin Wang","raw_affiliation_strings":["School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038647640","display_name":"Liang Chang","orcid":"https://orcid.org/0000-0002-6685-5576"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Chang","raw_affiliation_strings":["School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101440489","display_name":"Jun Zhou","orcid":"https://orcid.org/0000-0003-2098-9621"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Zhou","raw_affiliation_strings":["School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China"],"affiliations":[{"raw_affiliation_string":"School of lnformation and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100346548"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":0.4885,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.67212812,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"61","last_page":"62"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9998000264167786,"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/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/T10036","display_name":"Advanced Neural Network Applications","score":0.9987999796867371,"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/computer-science","display_name":"Computer science","score":0.8172320127487183},{"id":"https://openalex.org/keywords/field-programmable-gate-array","display_name":"Field-programmable gate array","score":0.7662367820739746},{"id":"https://openalex.org/keywords/hardware-acceleration","display_name":"Hardware acceleration","score":0.7503807544708252},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.588680624961853},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.5693371295928955},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5275328159332275},{"id":"https://openalex.org/keywords/software","display_name":"Software","score":0.5109823942184448},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.46793386340141296},{"id":"https://openalex.org/keywords/hardware-architecture","display_name":"Hardware architecture","score":0.46752145886421204},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4549751281738281},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.44970154762268066},{"id":"https://openalex.org/keywords/instruction-set","display_name":"Instruction set","score":0.42676621675491333},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.4179422855377197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3554726541042328},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.32381972670555115},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.27707549929618835},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.17292511463165283}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8172320127487183},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.7662367820739746},{"id":"https://openalex.org/C13164978","wikidata":"https://www.wikidata.org/wiki/Q600158","display_name":"Hardware acceleration","level":3,"score":0.7503807544708252},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.588680624961853},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.5693371295928955},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5275328159332275},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.5109823942184448},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.46793386340141296},{"id":"https://openalex.org/C65232700","wikidata":"https://www.wikidata.org/wiki/Q5656403","display_name":"Hardware architecture","level":3,"score":0.46752145886421204},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4549751281738281},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.44970154762268066},{"id":"https://openalex.org/C202491316","wikidata":"https://www.wikidata.org/wiki/Q272683","display_name":"Instruction set","level":2,"score":0.42676621675491333},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.4179422855377197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3554726541042328},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.32381972670555115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27707549929618835},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.17292511463165283},{"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/icta50426.2020.9331957","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icta50426.2020.9331957","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Integrated Circuits, Technologies and Applications (ICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8700000047683716,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1991113069","https://openalex.org/W2608058963","https://openalex.org/W2763160469","https://openalex.org/W2963387436","https://openalex.org/W3004820526"],"related_works":["https://openalex.org/W2518118925","https://openalex.org/W3159273459","https://openalex.org/W4383503138","https://openalex.org/W2281932057","https://openalex.org/W3131592046","https://openalex.org/W2010977501","https://openalex.org/W2009779270","https://openalex.org/W4391536292","https://openalex.org/W3170442433","https://openalex.org/W3214999411"],"abstract_inverted_index":{"Level":[0],"set":[1,27,45,83,132],"algorithm":[2,28,46,133],"has":[3],"been":[4],"widely":[5],"used":[6],"for":[7,86],"image":[8,22,87,100],"segmentation":[9,23],"due":[10],"to":[11,18,125,129],"its":[12],"high":[13],"accuracy.":[14],"In":[15,75],"addition,":[16],"compared":[17,128],"the":[19,25,38,42,64,116,130],"deep":[20],"learning-based":[21],"methods,":[24],"level":[26,44,82,131],"can":[29],"be":[30],"implemented":[31],"without":[32],"training":[33],"data,":[34],"which":[35],"significantly":[36],"reduce":[37],"labelling":[39],"efforts.":[40],"However,":[41],"normal":[43],"is":[47],"still":[48],"developed":[49],"using":[50],"software,":[51],"involving":[52],"complex":[53],"computation":[54],"with":[55,137],"a":[56,80],"large":[57,72],"number":[58],"of":[59],"pixels":[60],"and":[61,71,106,110],"iterations.":[62],"Also,":[63],"software":[65],"implementation":[66],"induces":[67],"long":[68],"processing":[69,104,112],"time":[70,107],"power":[73,141],"consumption.":[74,142],"this":[76],"work,":[77],"we":[78],"propose":[79],"FPGA-based":[81],"hardware":[84,91,121],"accelerator":[85,122],"segmentation.":[88],"The":[89],"proposed":[90,120],"accelerators":[92],"contain":[93],"four":[94],"design":[95],"components:":[96],"task-level":[97],"parallel":[98],"processing,":[99,102],"splitting":[101],"fully-pipelined":[103],"architecture,":[105],"multiplexed":[108],"gradient":[109],"divergence":[111],"engine.":[113],"Based":[114],"on":[115,135],"experimental":[117],"results,":[118],"our":[119],"achieves":[123],"up":[124],"10.7\u00d7":[126],"acceleration":[127],"executing":[134],"CPU,":[136],"only":[138],"2.2":[139],"W":[140]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}