{"id":"https://openalex.org/W4400276158","doi":"https://doi.org/10.1109/wcnc57260.2024.10571312","title":"Spiking-UNet: Spiking Neural Networks for Spectrum Occupancy Monitoring","display_name":"Spiking-UNet: Spiking Neural Networks for Spectrum Occupancy Monitoring","publication_year":2024,"publication_date":"2024-04-21","ids":{"openalex":"https://openalex.org/W4400276158","doi":"https://doi.org/10.1109/wcnc57260.2024.10571312"},"language":"en","primary_location":{"id":"doi:10.1109/wcnc57260.2024.10571312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc57260.2024.10571312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","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/A5057353421","display_name":"Kosta Dakic","orcid":"https://orcid.org/0000-0002-3078-7698"},"institutions":[{"id":"https://openalex.org/I4394709116","display_name":"UNSW Canberra","ror":"https://ror.org/0125wpx05","country_code":null,"type":"education","lineage":["https://openalex.org/I31746571","https://openalex.org/I4394709116"]},{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Kosta Dakic","raw_affiliation_strings":["School of Engineering & Technology, UNSW Canberra,Canberra,Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering & Technology, UNSW Canberra,Canberra,Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I4394709116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068318726","display_name":"Bassel Al Homssi","orcid":"https://orcid.org/0000-0002-7125-6738"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Bassel Al Homssi","raw_affiliation_strings":["School of Engineering, RMIT University,Melbourne,Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering, RMIT University,Melbourne,Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083386976","display_name":"Akram Al\u2010Hourani","orcid":"https://orcid.org/0000-0003-0652-8626"},"institutions":[{"id":"https://openalex.org/I4394709116","display_name":"UNSW Canberra","ror":"https://ror.org/0125wpx05","country_code":null,"type":"education","lineage":["https://openalex.org/I31746571","https://openalex.org/I4394709116"]},{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Akram Al-Hourani","raw_affiliation_strings":["School of Engineering & Technology, UNSW Canberra,Canberra,Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering & Technology, UNSW Canberra,Canberra,Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I4394709116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5057353421"],"corresponding_institution_ids":["https://openalex.org/I188329596","https://openalex.org/I4394709116"],"apc_list":null,"apc_paid":null,"fwci":1.7405,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.86562567,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9994999766349792,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9994999766349792,"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/occupancy","display_name":"Occupancy","score":0.8974946141242981},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.6654528379440308},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6161978840827942},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42601585388183594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.26311153173446655},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09161704778671265}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.8974946141242981},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6654528379440308},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6161978840827942},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42601585388183594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.26311153173446655},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09161704778671265},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcnc57260.2024.10571312","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcnc57260.2024.10571312","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Wireless Communications and Networking Conference (WCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1985940938","https://openalex.org/W2031211320","https://openalex.org/W2150397642","https://openalex.org/W2172139273","https://openalex.org/W2856895593","https://openalex.org/W2916238263","https://openalex.org/W2955338161","https://openalex.org/W2971778960","https://openalex.org/W2990878801","https://openalex.org/W2996687098","https://openalex.org/W3003514894","https://openalex.org/W3088404620","https://openalex.org/W3113412163","https://openalex.org/W3129643976","https://openalex.org/W3169469448","https://openalex.org/W3201870057","https://openalex.org/W3215401433","https://openalex.org/W4306827030","https://openalex.org/W4312909742","https://openalex.org/W4387682038","https://openalex.org/W4388819776","https://openalex.org/W4390691085"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W1968324288","https://openalex.org/W1540010871","https://openalex.org/W3023979140","https://openalex.org/W2904068067","https://openalex.org/W1565491139"],"abstract_inverted_index":{"With":[0],"the":[1,5,12,32,46,72,111],"exponential":[2],"growth":[3],"of":[4,7,34],"Internet":[6],"Things":[8],"(IoT)":[9],"landscape":[10],"and":[11,90,121],"resulting":[13],"spectrum":[14,19,29],"congestion,":[15],"innovative":[16],"techniques":[17,98,116],"for":[18,117],"monitoring":[20,30],"are":[21,59],"crucial.":[22],"This":[23],"paper":[24,78],"presents":[25],"an":[26],"approach":[27,75],"to":[28],"harnessing":[31],"power":[33],"spiking":[35],"neural":[36,96],"networks":[37],"(SNNs)":[38],"with":[39,66,93],"a":[40],"focus":[41],"on":[42],"image":[43],"segmentation":[44],"using":[45,113],"UNet":[47],"architecture.":[48],"Traditional":[49],"methods,":[50],"including":[51],"energy":[52,87,103],"detection,":[53],"have":[54],"been":[55],"widely":[56],"used":[57],"but":[58],"not":[60],"without":[61],"challenges,":[62],"especially":[63],"in":[64,76],"environments":[65],"varying":[67],"signal-to-noise":[68],"ratios.":[69],"In":[70],"contrast,":[71],"presented":[73],"SNN":[74],"this":[77],"demonstrates":[79],"through":[80],"simulations":[81],"performance":[82],"metrics":[83],"that":[84],"significantly":[85],"surpass":[86],"detection":[88],"methods":[89],"closely":[91],"align":[92],"conventional":[94],"convolutional":[95],"network":[97],"while":[99],"also":[100],"exhibiting":[101],"favorable":[102],"efficiency.":[104],"Future":[105],"explorations":[106],"will":[107],"delve":[108],"into":[109],"enhancing":[110],"framework":[112],"machine":[114],"learning":[115],"advanced":[118],"feature":[119],"extraction":[120],"multiclass":[122],"segmentation.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}