iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.openalex.org/works/doi:10.1109/IJCNN.2019.8852277
{"id":"https://openalex.org/W2977755543","doi":"https://doi.org/10.1109/ijcnn.2019.8852277","title":"Estimating Betti Numbers Using Deep Learning","display_name":"Estimating Betti Numbers Using Deep Learning","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977755543","doi":"https://doi.org/10.1109/ijcnn.2019.8852277","mag":"2977755543"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852277","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-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/A5006513001","display_name":"Rahul Paul","orcid":"https://orcid.org/0000-0003-1491-1166"},"institutions":[{"id":"https://openalex.org/I78757542","display_name":"University of Newcastle Australia","ror":"https://ror.org/00eae9z71","country_code":"AU","type":"education","lineage":["https://openalex.org/I78757542"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Rahul Paul","raw_affiliation_strings":["Interdisciplinary Machine Learning Research Group School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Interdisciplinary Machine Learning Research Group School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia","institution_ids":["https://openalex.org/I78757542"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054614441","display_name":"Stephan K. Chalup","orcid":"https://orcid.org/0000-0002-7886-3653"},"institutions":[{"id":"https://openalex.org/I78757542","display_name":"University of Newcastle Australia","ror":"https://ror.org/00eae9z71","country_code":"AU","type":"education","lineage":["https://openalex.org/I78757542"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Stephan Chalup","raw_affiliation_strings":["Interdisciplinary Machine Learning Research Group School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"Interdisciplinary Machine Learning Research Group School of Electrical Engineering and Computing, The University of Newcastle, Callaghan, NSW, Australia","institution_ids":["https://openalex.org/I78757542"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.287155,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":70,"max":74},"biblio":{"volume":"200","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T12536","display_name":"Topological Data Analysis in Science and Engineering","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12536","display_name":"Topological Data Analysis in Science and Engineering","score":0.9999,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T12859","display_name":"Advanced Techniques in Bioimage Analysis and Microscopy","score":0.9249,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/topological-data-analysis","display_name":"Topological data analysis","score":0.73006254},{"id":"https://openalex.org/keywords/statistical-topology","display_name":"Statistical Topology","score":0.555178},{"id":"https://openalex.org/keywords/topological-methods","display_name":"Topological Methods","score":0.531727},{"id":"https://openalex.org/keywords/shape-analysis","display_name":"Shape Analysis","score":0.501062},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine Learning","score":0.500771},{"id":"https://openalex.org/keywords/persistent-homology","display_name":"Persistent Homology","score":0.500242},{"id":"https://openalex.org/keywords/computational-topology","display_name":"Computational topology","score":0.4956168},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.48166883}],"concepts":[{"id":"https://openalex.org/C2874115","wikidata":"https://www.wikidata.org/wiki/Q17099562","display_name":"Persistent homology","level":2,"score":0.90272117},{"id":"https://openalex.org/C129621563","wikidata":"https://www.wikidata.org/wiki/Q429593","display_name":"Betti number","level":2,"score":0.80362827},{"id":"https://openalex.org/C2776477805","wikidata":"https://www.wikidata.org/wiki/Q4460773","display_name":"Topological data analysis","level":2,"score":0.73006254},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6148383},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.61191136},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5702075},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.56491154},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5636221},{"id":"https://openalex.org/C181576044","wikidata":"https://www.wikidata.org/wiki/Q4129926","display_name":"Computational topology","level":3,"score":0.4956168},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.48166883},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44963405},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4396254},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.43351793},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.42546445},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41043225},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38795096},{"id":"https://openalex.org/C184720557","wikidata":"https://www.wikidata.org/wiki/Q7825049","display_name":"Topology (electrical circuits)","level":2,"score":0.3827773},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32678968},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28670862},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.10632262},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C110521144","wikidata":"https://www.wikidata.org/wiki/Q193460","display_name":"Scalar field","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8852277","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"conference"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[],"grants":[],"datasets":[],"versions":[],"referenced_works_count":32,"referenced_works":["https://openalex.org/W107886322","https://openalex.org/W1523441917","https://openalex.org/W1991566301","https://openalex.org/W2071391326","https://openalex.org/W2072149862","https://openalex.org/W2096736341","https://openalex.org/W2148676644","https://openalex.org/W2150769593","https://openalex.org/W2187925611","https://openalex.org/W2467389505","https://openalex.org/W2555661991","https://openalex.org/W2557283755","https://openalex.org/W2618530766","https://openalex.org/W2733638363","https://openalex.org/W2734579475","https://openalex.org/W2741292700","https://openalex.org/W2766447205","https://openalex.org/W2774327564","https://openalex.org/W2799305483","https://openalex.org/W2892377642","https://openalex.org/W2900215683","https://openalex.org/W2962706934","https://openalex.org/W2964007201","https://openalex.org/W2964237352","https://openalex.org/W3040586665","https://openalex.org/W309757241","https://openalex.org/W3098455240","https://openalex.org/W3140579943","https://openalex.org/W3146195181","https://openalex.org/W4206669586","https://openalex.org/W4243494807","https://openalex.org/W4249449974"],"related_works":["https://openalex.org/W4388682440","https://openalex.org/W4286971133","https://openalex.org/W4213033583","https://openalex.org/W3212961654","https://openalex.org/W3210518039","https://openalex.org/W3199064261","https://openalex.org/W3198723315","https://openalex.org/W3137290046","https://openalex.org/W2942061931","https://openalex.org/W2567662842"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"an":[3,44],"efficient":[4,93],"computational":[5],"approach":[6,46,67,135],"for":[7,104],"estimating":[8,140],"the":[9,27,69,110,141],"topology":[10],"of":[11,29,55,71,76,101,121,143],"manifold":[12],"data":[13,75,108,123],"as":[14],"it":[15],"may":[16],"occur":[17],"in":[18,64,148,155],"applications.":[19],"For":[20],"two-":[21,105],"or":[22],"three-dimensional":[23,107],"point":[24,59],"cloud":[25],"data,":[26,88],"computation":[28],"Betti":[30,53,119],"numbers":[31,54,120,142],"using":[32],"persistent":[33],"homology":[34],"tools":[35],"can":[36,90,117],"already":[37],"be":[38,91,137],"computationally":[39,92],"very":[40],"expensive.":[41],"We":[42],"propose":[43],"alternative":[45],"that":[47,112,124],"employs":[48],"deep":[49,81,113],"learning":[50],"to":[51,96,151],"estimate":[52,118],"manifolds":[56,150],"approximated":[57],"by":[58],"clouds.":[60],"A":[61],"critical":[62],"aspect":[63],"this":[65,87],"new":[66],"is":[68],"generation":[70],"suitable":[72],"synthetic":[73],"training":[74],"scalable":[77],"topological":[78,127],"complexity.":[79],"Once":[80],"neural":[82,115],"networks":[83,116],"are":[84],"trained":[85],"on":[86],"inference":[89],"and":[94,106,146],"robust":[95],"noise.":[97],"The":[98,134],"pilot":[99],"results":[100],"our":[102],"study":[103],"support":[109],"hypothesis":[111],"convolutional":[114],"simulated":[122],"has":[125],"a":[126],"complexity":[128],"beyond":[129,139],"immediate":[130],"human":[131],"visual":[132],"comprehension.":[133],"could":[136],"generalised":[138],"holes,":[144],"cavities":[145],"tunnels":[147],"low-dimensional":[149],"counting":[152],"high-dimensional":[153,156],"holes":[154],"data.":[157]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2977755543","counts_by_year":[{"year":2023,"cited_by_count":2}],"updated_date":"2024-11-22T17:43:29.217121","created_date":"2019-10-10"}