{"id":"https://openalex.org/W3173062185","doi":"https://doi.org/10.1007/s11063-021-10544-4","title":"A Neural Network Based System for Efficient Semantic Segmentation of Radar Point Clouds","display_name":"A Neural Network Based System for Efficient Semantic Segmentation of Radar Point Clouds","publication_year":2021,"publication_date":"2021-05-29","ids":{"openalex":"https://openalex.org/W3173062185","doi":"https://doi.org/10.1007/s11063-021-10544-4","mag":"3173062185"},"language":"en","primary_location":{"id":"doi:10.1007/s11063-021-10544-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-021-10544-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-021-10544-4.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11063-021-10544-4.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5051071107","display_name":"Alessandro Cennamo","orcid":"https://orcid.org/0000-0001-6475-1354"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]},{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Alessandro Cennamo","raw_affiliation_strings":["Aptiv Services Deutschland GmbH, 42199, Wuppertal, North Rhine-Westphalia, Germany","University of Wuppertal (BUW), 42199, Wuppertal, North Rhine-Westphalia, Germany"],"raw_orcid":"https://orcid.org/0000-0001-6475-1354","affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, 42199, Wuppertal, North Rhine-Westphalia, Germany","institution_ids":["https://openalex.org/I4210130520"]},{"raw_affiliation_string":"University of Wuppertal (BUW), 42199, Wuppertal, North Rhine-Westphalia, Germany","institution_ids":["https://openalex.org/I167360494"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003561019","display_name":"Florian Kaestner","orcid":null},"institutions":[{"id":"https://openalex.org/I4210130520","display_name":"Aptiv (Germany)","ror":"https://ror.org/039sb8791","country_code":"DE","type":"company","lineage":["https://openalex.org/I4210107152","https://openalex.org/I4210130520"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Kaestner","raw_affiliation_strings":["Aptiv Services Deutschland GmbH, 42199, Wuppertal, North Rhine-Westphalia, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aptiv Services Deutschland GmbH, 42199, Wuppertal, North Rhine-Westphalia, Germany","institution_ids":["https://openalex.org/I4210130520"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080666933","display_name":"Anton Kummert","orcid":"https://orcid.org/0000-0002-0282-5087"},"institutions":[{"id":"https://openalex.org/I167360494","display_name":"University of Wuppertal","ror":"https://ror.org/00613ak93","country_code":"DE","type":"education","lineage":["https://openalex.org/I167360494"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Anton Kummert","raw_affiliation_strings":["University of Wuppertal (BUW), 42199, Wuppertal, North Rhine-Westphalia, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Wuppertal (BUW), 42199, Wuppertal, North Rhine-Westphalia, Germany","institution_ids":["https://openalex.org/I167360494"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5051071107"],"corresponding_institution_ids":["https://openalex.org/I167360494","https://openalex.org/I4210130520"],"apc_list":{"value":2390,"currency":"EUR","value_usd":2990},"apc_paid":{"value":2390,"currency":"EUR","value_usd":2990},"fwci":0.3107,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.4840745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"53","issue":"5","first_page":"3217","last_page":"3235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9829000234603882,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9735000133514404,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7611110210418701},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.6869903206825256},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6556667685508728},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6404728889465332},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6034519672393799},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5173720717430115},{"id":"https://openalex.org/keywords/computational-intelligence","display_name":"Computational intelligence","score":0.42976540327072144},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4104689359664917},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3836979269981384},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38008394837379456},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.09148508310317993}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7611110210418701},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.6869903206825256},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6556667685508728},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6404728889465332},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6034519672393799},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5173720717430115},{"id":"https://openalex.org/C139502532","wikidata":"https://www.wikidata.org/wiki/Q1122090","display_name":"Computational intelligence","level":2,"score":0.42976540327072144},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4104689359664917},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3836979269981384},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38008394837379456},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.09148508310317993},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11063-021-10544-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-021-10544-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-021-10544-4.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11063-021-10544-4","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11063-021-10544-4","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11063-021-10544-4.pdf","source":{"id":"https://openalex.org/S140962798","display_name":"Neural Processing Letters","issn_l":"1370-4621","issn":["1370-4621","1573-773X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Neural Processing Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.6399999856948853,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320313454","display_name":"Bergische Universit\u00e4t Wuppertal","ror":"https://ror.org/00613ak93"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3173062185.pdf","grobid_xml":"https://content.openalex.org/works/W3173062185.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W1673310716","https://openalex.org/W2064675550","https://openalex.org/W2120010140","https://openalex.org/W2141723408","https://openalex.org/W2164500538","https://openalex.org/W2327992289","https://openalex.org/W2469609794","https://openalex.org/W2560609797","https://openalex.org/W2581082771","https://openalex.org/W2611781169","https://openalex.org/W2741069557","https://openalex.org/W2753798143","https://openalex.org/W2774756930","https://openalex.org/W2799162093","https://openalex.org/W2891649842","https://openalex.org/W2896175616","https://openalex.org/W2902302021","https://openalex.org/W2908882634","https://openalex.org/W2911964244","https://openalex.org/W2940791172","https://openalex.org/W2963121255","https://openalex.org/W2963351448","https://openalex.org/W2963721253","https://openalex.org/W2963727135","https://openalex.org/W2968370607","https://openalex.org/W3004332731","https://openalex.org/W3012291630","https://openalex.org/W3029530394","https://openalex.org/W3032668181","https://openalex.org/W3035574168","https://openalex.org/W3169902865","https://openalex.org/W6603768312"],"related_works":["https://openalex.org/W3016928466","https://openalex.org/W4389574804","https://openalex.org/W2936725271","https://openalex.org/W3150655618","https://openalex.org/W2295788148","https://openalex.org/W1578717197","https://openalex.org/W3108295644","https://openalex.org/W2626737336","https://openalex.org/W2005998065","https://openalex.org/W2114282491"],"abstract_inverted_index":{"Abstract":[0],"The":[1],"last":[2],"decade":[3],"has":[4],"witnessed":[5],"important":[6],"advancements":[7],"in":[8,29],"the":[9,89,111,113,131],"field":[10],"of":[11],"computer":[12],"vision":[13],"and":[14],"scene":[15],"understanding,":[16],"enabling":[17],"applications":[18],"such":[19],"us":[20],"autonomous":[21],"vehicles.":[22],"Radar":[23],"is":[24],"a":[25,49,87,103],"commonly":[26],"adopted":[27],"sensor":[28],"automotive":[30],"industry,":[31],"but":[32],"its":[33],"suitability":[34],"to":[35,55,97,115],"machine":[36,104],"learning":[37,105],"techniques":[38],"still":[39],"remains":[40],"an":[41,63,94],"open":[42],"question.":[43],"In":[44],"this":[45],"work,":[46],"we":[47,101],"propose":[48,102],"neural":[50],"network":[51,112],"(NN)":[52],"based":[53],"solution":[54],"efficiently":[56],"process":[57],"radar":[58,72,106,118],"data.":[59],"We":[60,120],"introduce":[61],"RadarPCNN,":[62],"architecture":[64],"specifically":[65],"designed":[66],"for":[67],"performing":[68],"semantic":[69],"segmentation":[70],"on":[71],"point":[73],"clouds.":[74],"It":[75],"uses":[76],"PointNet":[77],"$$++$$":[78],"<mml:math":[79],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\">":[80],"<mml:mrow>":[81],"<mml:mo>+</mml:mo>":[82,83],"</mml:mrow>":[84],"</mml:math>":[85],"as":[86],"building-block\u2014enhancing":[88],"sampling":[90],"stage":[91],"with":[92],"mean-shift\u2014and":[93],"attention":[95],"mechanism":[96],"fuse":[98],"information.":[99],"Additionally,":[100],"pre-processing":[107],"module":[108],"that":[109,122],"confers":[110],"ability":[114],"learn":[116],"from":[117],"features.":[119],"show":[121],"our":[123],"solutions":[124],"are":[125],"effective,":[126],"yielding":[127],"superior":[128],"performance":[129],"than":[130],"state-of-the-art.":[132]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3}],"updated_date":"2026-07-16T13:24:37.021932","created_date":"2025-10-10T00:00:00"}