{"id":"https://openalex.org/W4200258607","doi":"https://doi.org/10.1109/sensors47087.2021.9639553","title":"A Model to Predict Mass Spectrum from Odor Impression using Deep Neural Network","display_name":"A Model to Predict Mass Spectrum from Odor Impression using Deep Neural Network","publication_year":2021,"publication_date":"2021-10-31","ids":{"openalex":"https://openalex.org/W4200258607","doi":"https://doi.org/10.1109/sensors47087.2021.9639553"},"language":"en","primary_location":{"id":"doi:10.1109/sensors47087.2021.9639553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sensors47087.2021.9639553","pdf_url":null,"source":{"id":"https://openalex.org/S4363605007","display_name":"2021 IEEE Sensors","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Sensors","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/A5055839487","display_name":"Daisuke Hasebe","orcid":null},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisuke Hasebe","raw_affiliation_strings":["Tokyo Institute of Technology, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Kanagawa, Japan","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026237845","display_name":"Takamichi Nakamoto","orcid":"https://orcid.org/0000-0002-0599-226X"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takamichi Nakamoto","raw_affiliation_strings":["Tokyo Institute of Technology, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology, Kanagawa, Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7234,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.375,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10971","display_name":"Olfactory and Sensory Function Studies","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2809","display_name":"Sensory Systems"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12321","display_name":"Insect Pheromone Research and Control","score":0.9610000252723694,"subfield":{"id":"https://openalex.org/subfields/1109","display_name":"Insect Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/odor","display_name":"Odor","score":0.9371255040168762},{"id":"https://openalex.org/keywords/impression","display_name":"Impression","score":0.824285626411438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6936444044113159},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5958821177482605},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.5264440774917603},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5113665461540222},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5075646638870239},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1363457441329956}],"concepts":[{"id":"https://openalex.org/C2778916471","wikidata":"https://www.wikidata.org/wiki/Q485537","display_name":"Odor","level":2,"score":0.9371255040168762},{"id":"https://openalex.org/C2776684213","wikidata":"https://www.wikidata.org/wiki/Q6007582","display_name":"Impression","level":2,"score":0.824285626411438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6936444044113159},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5958821177482605},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.5264440774917603},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5113665461540222},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5075646638870239},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1363457441329956},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sensors47087.2021.9639553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sensors47087.2021.9639553","pdf_url":null,"source":{"id":"https://openalex.org/S4363605007","display_name":"2021 IEEE Sensors","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":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Sensors","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":6,"referenced_works":["https://openalex.org/W2472841255","https://openalex.org/W2507164429","https://openalex.org/W2761485135","https://openalex.org/W3112448767","https://openalex.org/W3113375759","https://openalex.org/W3159898350"],"related_works":["https://openalex.org/W2085677935","https://openalex.org/W2327021330","https://openalex.org/W2389617532","https://openalex.org/W2397440126","https://openalex.org/W2316594088","https://openalex.org/W2184842172","https://openalex.org/W2409084359","https://openalex.org/W68571419","https://openalex.org/W2057749067","https://openalex.org/W3155832235"],"abstract_inverted_index":{"Due":[0],"to":[1,11,21,49,99],"the":[2,26,47,61,72],"complexity":[3],"of":[4],"odor":[5,17,23,31,56,77,93,96],"perception,":[6],"it":[7],"has":[8,42],"been":[9,43],"difficult":[10],"predict":[12,30,50],"odorant":[13],"molecular":[14],"structure":[15],"or":[16],"sensing":[18],"data":[19],"corresponding":[20],"human":[22],"perception.":[24],"On":[25],"contrary,":[27],"we":[28,45,68,86],"can":[29,69,87],"impression":[32,57,78],"from":[33,54,76,91],"mass":[34,51,73,89],"spectrum":[35,52,74,90],"using":[36,80],"DNN.":[37],"Since":[38],"its":[39],"prediction":[40],"accuracy":[41],"improved,":[44],"propose":[46],"method":[48,83],"features":[53],"specified":[55],"based":[58],"on":[59],"solving":[60],"inverse":[62],"problem.":[63],"It":[64],"is":[65],"found":[66],"that":[67,85],"accurately":[70],"obtain":[71,88],"feature":[75],"scores":[79],"gradient":[81],"descent":[82],"and":[84],"modified":[92],"evaluation":[94],"when":[95],"descriptors":[97],"correlate":[98],"each":[100],"other.":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
