{"id":"https://openalex.org/W2988516737","doi":"https://doi.org/10.1109/access.2019.2950643","title":"Graph Spectral Domain Feature Learning With Application to in-Air Hand-Drawn Number and Shape Recognition","display_name":"Graph Spectral Domain Feature Learning With Application to in-Air Hand-Drawn Number and Shape Recognition","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2988516737","doi":"https://doi.org/10.1109/access.2019.2950643","mag":"2988516737"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2950643","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950643","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08888161.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08888161.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009835688","display_name":"Basheer Alwaely","orcid":"https://orcid.org/0000-0002-1845-2641"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Basheer Alwaely","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035952586","display_name":"Charith Abhayaratne","orcid":"https://orcid.org/0000-0002-2799-7395"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Charith Abhayaratne","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K"],"raw_orcid":"https://orcid.org/0000-0002-2799-7395","affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I91136226"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.6948,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.75262542,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"159661","last_page":"159673"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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/T12292","display_name":"Graph Theory and Algorithms","score":0.9987000226974487,"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":0.9976000189781189,"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/adjacency-matrix","display_name":"Adjacency matrix","score":0.7007280588150024},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.6725079417228699},{"id":"https://openalex.org/keywords/laplacian-matrix","display_name":"Laplacian matrix","score":0.6282058358192444},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6060107946395874},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5897839665412903},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5736088752746582},{"id":"https://openalex.org/keywords/adjacency-list","display_name":"Adjacency list","score":0.5623511075973511},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5005896091461182},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4595263600349426},{"id":"https://openalex.org/keywords/spectral-graph-theory","display_name":"Spectral graph theory","score":0.43418222665786743},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4324409067630768},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41403743624687195},{"id":"https://openalex.org/keywords/graph-energy","display_name":"Graph energy","score":0.4122403562068939},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.39159542322158813},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28011029958724976},{"id":"https://openalex.org/keywords/voltage-graph","display_name":"Voltage graph","score":0.2545285224914551},{"id":"https://openalex.org/keywords/line-graph","display_name":"Line graph","score":0.21347662806510925}],"concepts":[{"id":"https://openalex.org/C180356752","wikidata":"https://www.wikidata.org/wiki/Q727035","display_name":"Adjacency matrix","level":3,"score":0.7007280588150024},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.6725079417228699},{"id":"https://openalex.org/C115178988","wikidata":"https://www.wikidata.org/wiki/Q772067","display_name":"Laplacian matrix","level":3,"score":0.6282058358192444},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6060107946395874},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5897839665412903},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5736088752746582},{"id":"https://openalex.org/C110484373","wikidata":"https://www.wikidata.org/wiki/Q264398","display_name":"Adjacency list","level":2,"score":0.5623511075973511},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5005896091461182},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4595263600349426},{"id":"https://openalex.org/C74003402","wikidata":"https://www.wikidata.org/wiki/Q3180727","display_name":"Spectral graph theory","level":5,"score":0.43418222665786743},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4324409067630768},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41403743624687195},{"id":"https://openalex.org/C78913703","wikidata":"https://www.wikidata.org/wiki/Q5597087","display_name":"Graph energy","level":5,"score":0.4122403562068939},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39159542322158813},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28011029958724976},{"id":"https://openalex.org/C22149727","wikidata":"https://www.wikidata.org/wiki/Q7940747","display_name":"Voltage graph","level":4,"score":0.2545285224914551},{"id":"https://openalex.org/C203776342","wikidata":"https://www.wikidata.org/wiki/Q1378376","display_name":"Line graph","level":3,"score":0.21347662806510925},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/access.2019.2950643","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950643","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08888161.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:153887","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"},{"id":"pmh:oai:doaj.org/article:cbec25e610314ed9a4826aac274a7dc9","is_oa":true,"landing_page_url":"https://doaj.org/article/cbec25e610314ed9a4826aac274a7dc9","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 159661-159673 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2950643","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2950643","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08888161.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2988516737.pdf","grobid_xml":"https://content.openalex.org/works/W2988516737.grobid-xml"},"referenced_works_count":64,"referenced_works":["https://openalex.org/W569942085","https://openalex.org/W1781665229","https://openalex.org/W1965574731","https://openalex.org/W1969595749","https://openalex.org/W1972278541","https://openalex.org/W1985106404","https://openalex.org/W2003538563","https://openalex.org/W2004991485","https://openalex.org/W2008109610","https://openalex.org/W2009732386","https://openalex.org/W2021591831","https://openalex.org/W2035679901","https://openalex.org/W2038377170","https://openalex.org/W2046304388","https://openalex.org/W2062280721","https://openalex.org/W2074032690","https://openalex.org/W2074516110","https://openalex.org/W2078030028","https://openalex.org/W2098272070","https://openalex.org/W2101491865","https://openalex.org/W2107940287","https://openalex.org/W2108182844","https://openalex.org/W2121225280","https://openalex.org/W2121947440","https://openalex.org/W2130635921","https://openalex.org/W2132914434","https://openalex.org/W2137745668","https://openalex.org/W2142651208","https://openalex.org/W2144596745","https://openalex.org/W2147394543","https://openalex.org/W2158256890","https://openalex.org/W2158787690","https://openalex.org/W2159620287","https://openalex.org/W2159808202","https://openalex.org/W2162899276","https://openalex.org/W2164109418","https://openalex.org/W2166820607","https://openalex.org/W2171105099","https://openalex.org/W2219948256","https://openalex.org/W2238782374","https://openalex.org/W2271488822","https://openalex.org/W2343424255","https://openalex.org/W2343970360","https://openalex.org/W2414757501","https://openalex.org/W2478475484","https://openalex.org/W2536726338","https://openalex.org/W2543872873","https://openalex.org/W2614818206","https://openalex.org/W2621076832","https://openalex.org/W2766137121","https://openalex.org/W2766703716","https://openalex.org/W2794219092","https://openalex.org/W2807258267","https://openalex.org/W2886140079","https://openalex.org/W2901183446","https://openalex.org/W2903140870","https://openalex.org/W2922016935","https://openalex.org/W2940081378","https://openalex.org/W2950103748","https://openalex.org/W2996830232","https://openalex.org/W6638222449","https://openalex.org/W6641617661","https://openalex.org/W6682759379","https://openalex.org/W6693942370"],"related_works":["https://openalex.org/W2549624392","https://openalex.org/W4293849741","https://openalex.org/W2614668157","https://openalex.org/W2346372059","https://openalex.org/W2001241184","https://openalex.org/W1533309322","https://openalex.org/W4352976663","https://openalex.org/W2963718991","https://openalex.org/W2576668423","https://openalex.org/W4298350343"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"the":[3,12,22,34,46,49,53,59,67,71,76,82,85,88,93,127,137,151],"problem":[4],"of":[5,7,45,48,52,84,87,92,117,140],"recognition":[6,109,152],"dynamic":[8,35],"shapes":[9,36],"by":[10,43],"representing":[11],"structure":[13,86],"in":[14,102],"a":[15,18,38],"shape":[16],"as":[17,79],"graph":[19,23,54,95],"and":[20,107,119,123,144,148,158],"learning":[21],"spectral":[24,96],"domain":[25,97],"features.":[26],"Our":[27],"proposed":[28,94],"method":[29,63],"includes":[30],"pre-processing":[31],"for":[32,57,74,121,130],"converting":[33],"into":[37],"fully":[39],"connected":[40],"graph,":[41],"followed":[42],"analysis":[44],"eigenvectors":[47],"normalized":[50],"Laplacian":[51],"adjacency":[55],"matrix":[56],"forming":[58],"feature":[60,77],"vectors.":[61],"The":[62,90],"proposes":[64],"to":[65,70,146,155],"use":[66,91],"eigenvector":[68],"corresponding":[69],"lowest":[72],"eigenvalue":[73],"formulating":[75],"vectors":[78],"it":[80],"captures":[81],"details":[83],"graph.":[89],"representation":[98],"has":[99,112,136],"been":[100],"demonstrated":[101],"an":[103],"in-air":[104],"hand-drawn":[105],"number":[106],"symbol":[108],"applications.":[110],"It":[111,134],"achieved":[113],"average":[114],"accuracy":[115],"rates":[116],"99.56%":[118],"99.44%,":[120],"numbers":[122],"symbols,":[124],"respectively,":[125],"outperforming":[126],"existing":[128],"methods":[129],"all":[131],"datasets":[132],"used.":[133],"also":[135],"added":[138],"benefits":[139],"fast":[141],"real-time":[142],"operation":[143],"invariance":[145],"rotation":[147],"flipping,":[149],"making":[150],"system":[153],"robust":[154],"different":[156],"writing":[157],"drawing":[159],"variations.":[160]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}