{"id":"https://openalex.org/W2902288183","doi":"https://doi.org/10.1109/snams.2018.8554487","title":"Transferable HMM Trained Matrices for Accelerating Statistical Segmentation Time","display_name":"Transferable HMM Trained Matrices for Accelerating Statistical Segmentation Time","publication_year":2018,"publication_date":"2018-10-01","ids":{"openalex":"https://openalex.org/W2902288183","doi":"https://doi.org/10.1109/snams.2018.8554487","mag":"2902288183"},"language":"en","primary_location":{"id":"doi:10.1109/snams.2018.8554487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snams.2018.8554487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS)","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/A5032974396","display_name":"Shadi AlZu\u2019bi","orcid":"https://orcid.org/0000-0003-4173-2323"},"institutions":[{"id":"https://openalex.org/I145019703","display_name":"Al-Zaytoonah University of Jordan","ror":"https://ror.org/04a5b0p13","country_code":"JO","type":"education","lineage":["https://openalex.org/I145019703"]}],"countries":["JO"],"is_corresponding":true,"raw_author_name":"Shadi AlZu'bi","raw_affiliation_strings":["Faculty of Sciences and Information Technology, AlZaytoonah University of Jordan, Amman, Jordan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Information Technology, AlZaytoonah University of Jordan, Amman, Jordan","institution_ids":["https://openalex.org/I145019703"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056714121","display_name":"Sokyna M. Al-Qatawneh","orcid":"https://orcid.org/0000-0002-1835-7804"},"institutions":[{"id":"https://openalex.org/I145019703","display_name":"Al-Zaytoonah University of Jordan","ror":"https://ror.org/04a5b0p13","country_code":"JO","type":"education","lineage":["https://openalex.org/I145019703"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Sokyna Al-Qatawneh","raw_affiliation_strings":["Faculty of Sciences and Information Technology, AlZaytoonah University of Jordan, Amman, Jordan"],"affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Information Technology, AlZaytoonah University of Jordan, Amman, Jordan","institution_ids":["https://openalex.org/I145019703"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059553043","display_name":"Mohammad Alsmirat","orcid":"https://orcid.org/0000-0002-1071-7713"},"institutions":[{"id":"https://openalex.org/I156983542","display_name":"Jordan University of Science and Technology","ror":"https://ror.org/03y8mtb59","country_code":"JO","type":"education","lineage":["https://openalex.org/I156983542"]}],"countries":["JO"],"is_corresponding":false,"raw_author_name":"Mohammad Alsmirat","raw_affiliation_strings":["Faculty of Information Technology, Jordan University of Science and Technology, Irbid, Jordan"],"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, Jordan University of Science and Technology, Irbid, Jordan","institution_ids":["https://openalex.org/I156983542"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5032974396"],"corresponding_institution_ids":["https://openalex.org/I145019703"],"apc_list":null,"apc_paid":null,"fwci":2.4025,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.92188699,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"172","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.9983000159263611,"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/T10862","display_name":"AI in cancer detection","score":0.9976000189781189,"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/hidden-markov-model","display_name":"Hidden Markov model","score":0.9040842056274414},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.8216792345046997},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8207540512084961},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6222459077835083},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5983651280403137},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5397208333015442},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5226913690567017},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46630561351776123},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.4122052490711212},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3462878167629242}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.9040842056274414},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8216792345046997},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8207540512084961},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6222459077835083},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5983651280403137},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5397208333015442},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5226913690567017},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46630561351776123},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.4122052490711212},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3462878167629242},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/snams.2018.8554487","is_oa":false,"landing_page_url":"https://doi.org/10.1109/snams.2018.8554487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Fifth International Conference on Social Networks Analysis, Management and Security (SNAMS)","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":53,"referenced_works":["https://openalex.org/W107968503","https://openalex.org/W157162179","https://openalex.org/W640294433","https://openalex.org/W1431586989","https://openalex.org/W1533959433","https://openalex.org/W1781215685","https://openalex.org/W1967551258","https://openalex.org/W1973880112","https://openalex.org/W1987983010","https://openalex.org/W2003192948","https://openalex.org/W2007754818","https://openalex.org/W2017049237","https://openalex.org/W2056968783","https://openalex.org/W2083927153","https://openalex.org/W2083942888","https://openalex.org/W2093834886","https://openalex.org/W2099290282","https://openalex.org/W2103535990","https://openalex.org/W2108102303","https://openalex.org/W2108859253","https://openalex.org/W2113076747","https://openalex.org/W2113622874","https://openalex.org/W2114977007","https://openalex.org/W2115242586","https://openalex.org/W2118386984","https://openalex.org/W2119391140","https://openalex.org/W2121111408","https://openalex.org/W2125838338","https://openalex.org/W2127093827","https://openalex.org/W2131386551","https://openalex.org/W2132803430","https://openalex.org/W2135056195","https://openalex.org/W2144429080","https://openalex.org/W2149098431","https://openalex.org/W2150903265","https://openalex.org/W2152947391","https://openalex.org/W2153233077","https://openalex.org/W2156260858","https://openalex.org/W2169958006","https://openalex.org/W2271546270","https://openalex.org/W2406304561","https://openalex.org/W2592929672","https://openalex.org/W2608184483","https://openalex.org/W2625370688","https://openalex.org/W2754160021","https://openalex.org/W2794303645","https://openalex.org/W3023408402","https://openalex.org/W3100816363","https://openalex.org/W4212781311","https://openalex.org/W6673940755","https://openalex.org/W6714031345","https://openalex.org/W6737388947","https://openalex.org/W6959411346"],"related_works":["https://openalex.org/W1974738623","https://openalex.org/W1986655823","https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W3011384228","https://openalex.org/W2945274617","https://openalex.org/W3199300986","https://openalex.org/W4313052709","https://openalex.org/W4298131179"],"abstract_inverted_index":{"Segmentation":[0],"problem":[1,95],"has":[2,110],"been":[3,12,42,65,111,168,182],"solved":[4],"in":[5,55,72,170],"the":[6,22,26,47,83,100,105,132,142,146,149,160,179,192],"last":[7],"decade,":[8],"many":[9],"techniques":[10,40,87],"have":[11,41,64,167,181],"implemented":[13],"to":[14,44,104,139,159],"discover":[15],"this":[16,124],"issue.":[17],"Many":[18],"problems":[19],"arise":[20],"during":[21],"segmentation":[23,48,86,165],"process":[24],"including":[25],"acceptable":[27],"error":[28],"rate,":[29],"low":[30],"quality":[31],"assessment,":[32],"and":[33,50,59,157],"time":[34,49,101,144],"complexity.":[35],"A":[36],"variety":[37],"of":[38,82,135,148,194,203],"acceleration":[39],"applied":[43],"speed":[45],"up":[46],"achieve":[51],"a":[52,90,128],"segmented":[53],"result":[54],"real":[56],"time.":[57,173],"GPU":[58],"parallel":[60],"processing":[61,172],"using":[62,113,198],"hardware":[63],"employed":[66],"efficiently":[67],"here,":[68],"but":[69,116],"still":[70,117],"limited":[71],"3D":[73,121,150],"images":[74,197],"segmentation.":[75],"Hidden":[76],"Markov":[77],"Model":[78],"(HMM)":[79],"is":[80,99,155],"one":[81],"best":[84],"statistical":[85],"that":[88],"played":[89],"significant":[91],"rule":[92],"recently.":[93],"The":[94],"associated":[96],"with":[97,120],"HMM":[98,136,153],"complexity":[102],"due":[103],"training":[106,143],"steps.":[107],"This":[108],"issue":[109],"resolved":[112],"different":[114],"accelerator":[115],"not":[118],"efficient":[119],"volumes.":[122],"In":[123],"research,":[125],"we":[126],"propose":[127],"methodology":[129],"for":[130,145,178],"transferring":[131],"trained":[133],"matrices":[134],"from":[137],"image":[138],"another":[140],"skipping":[141],"rest":[147],"volume.":[151,162],"One":[152],"train":[154],"generated":[156],"generalized":[158],"whole":[161],"An":[163],"accurate":[164],"results":[166],"achieved":[169,183],"less":[171],"And":[174],"fixed":[175],"class":[176,186],"belongings":[177],"pixels":[180],"without":[184],"any":[185],"membership":[187],"variations.":[188],"Which":[189],"will":[190],"increase":[191],"possibility":[193],"segmenting":[195],"medical":[196],"HMMs":[199],"on":[200],"GPUs":[201],"instead":[202],"CPUs.":[204]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":13},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
