{"id":"https://openalex.org/W7225189097","doi":"https://doi.org/10.5281/zenodo.23909416","title":"Aur quality prediction using deep learning","display_name":"Aur quality prediction using deep learning","publication_year":2026,"publication_date":"2026-11-03","ids":{"openalex":"https://openalex.org/W7225189097","doi":"https://doi.org/10.5281/zenodo.23909416"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.23909416","doi":"https://doi.org/10.5281/zenodo.23909416","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23909416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"volume":null,"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.23909416","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160462064","display_name":"Ibaad Shaikh","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shaikh, Ibaad","raw_affiliation_strings":["Maharashtra institute of technology aurangabad Maharashtra"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maharashtra institute of technology aurangabad Maharashtra","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160450357","display_name":"Nihal Tamboli","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tamboli, Nihal","raw_affiliation_strings":["Maharashtra institute of technology aurangabad Maharashtra"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maharashtra institute of technology aurangabad Maharashtra","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160348438","display_name":"Vaishali Gaikwad","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gaikwad, Vaishali","raw_affiliation_strings":["Maharashtra institute of technology aurangabad Maharashtra"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Maharashtra institute of technology aurangabad Maharashtra","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.75263713,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9970999956130981,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9970999956130981,"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/T10190","display_name":"Air Quality and Health Impacts","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"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":0.0003000000142492354,"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/air-quality-forecasting","display_name":"air quality forecasting","score":0.996999979019165},{"id":"https://openalex.org/keywords/air-pollution-classification","display_name":"air pollution classification","score":0.8209999799728394},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.8299999833106995},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.9919999837875366},{"id":"https://openalex.org/keywords/web-interface","display_name":"web interface","score":0.5180000066757202},{"id":"https://openalex.org/keywords/air-quality-index","display_name":"air quality index","score":0.5950000286102295}],"concepts":[{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.7696999907493591},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6917999982833862},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5834000110626221},{"id":"https://openalex.org/C126314574","wikidata":"https://www.wikidata.org/wiki/Q2364111","display_name":"Air quality index","level":2,"score":0.5719000101089478},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5716000199317932},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5372999906539917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4821000099182129},{"id":"https://openalex.org/C559116025","wikidata":"https://www.wikidata.org/wiki/Q131123","display_name":"Air pollution","level":2,"score":0.3889000117778778},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3776000142097473},{"id":"https://openalex.org/C113843644","wikidata":"https://www.wikidata.org/wiki/Q901882","display_name":"Interface (matter)","level":4,"score":0.3163999915122986},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2597000002861023}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.23909416","doi":"https://doi.org/10.5281/zenodo.23909416","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23909416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},{"id":"doi:10.5281/zenodo.23909417","doi":"https://doi.org/10.5281/zenodo.23909417","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23909417","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"}],"best_oa_location":{"id":"doi:10.5281/zenodo.23909416","doi":"https://doi.org/10.5281/zenodo.23909416","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.23909416","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article-journal"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7213598414","https://openalex.org/W7160955084","https://openalex.org/W7162673349","https://openalex.org/W7125103456","https://openalex.org/W7117988642","https://openalex.org/W7155630209","https://openalex.org/W7087347324","https://openalex.org/W7202179686","https://openalex.org/W7214914768","https://openalex.org/W7162837098"],"abstract_inverted_index":{"Air":[0],"Quality":[1],"Prediction":[2],"Using":[3],"Deep":[4],"Learning":[5],"is":[6],"a":[7],"machine":[8],"learning-based":[9],"project":[10],"that":[11],"analyzes":[12],"air":[13,18,46],"pollution":[14,47],"images":[15],"and":[16,32,38,49],"classifies":[17],"quality":[19],"into":[20],"six":[21],"categories:":[22],"Good,":[23],"Moderate,":[24],"Unhealthy":[25],"for":[26,55],"Sensitive":[27],"Groups,":[28],"Unhealthy,":[29,31],"Very":[30],"Severe.":[33],"It":[34],"uses":[35],"deep":[36],"learning":[37,43],"CNN-based":[39],"models":[40],"with":[41],"transfer":[42],"to":[44],"predict":[45],"levels":[48],"provides":[50],"an":[51],"easy-to-use":[52],"web":[53],"interface":[54],"displaying":[56],"prediction":[57],"results.":[58]},"counts_by_year":[],"updated_date":"2026-11-05T12:25:35.769452","created_date":"2026-11-04T00:00:00"}