{"id":"https://openalex.org/W7157354814","doi":"https://doi.org/10.48550/arxiv.2604.23542","title":"AusSmoke meets MultiNatSmoke: a fully-labelled diverse smoke segmentation dataset","display_name":"AusSmoke meets MultiNatSmoke: a fully-labelled diverse smoke segmentation dataset","publication_year":2026,"publication_date":"2026-04-26","ids":{"openalex":"https://openalex.org/W7157354814","doi":"https://doi.org/10.48550/arxiv.2604.23542"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.23542","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23542","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.23542","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134790468","display_name":"Weihao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Weihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134796013","display_name":"Hongjin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Hongjin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101788641","display_name":"Gao Zhu","orcid":"https://orcid.org/0000-0002-6635-8836"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhu, Gao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001285878","display_name":"Ge-Peng Ji","orcid":"https://orcid.org/0000-0001-7092-2877"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ji, Ge-Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042575361","display_name":"Nicholas Wilson","orcid":"https://orcid.org/0000-0002-3813-5950"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wilson, Nicholas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134776741","display_name":"Marta Yebra","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yebra, Marta","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134807220","display_name":"Nick Barnes","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barnes, Nick","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10555","display_name":"Fire effects on ecosystems","score":0.005499999970197678,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.0017000000225380063,"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/segmentation","display_name":"Segmentation","score":0.7511000037193298},{"id":"https://openalex.org/keywords/smoke","display_name":"Smoke","score":0.4948999881744385},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.48570001125335693},{"id":"https://openalex.org/keywords/scarcity","display_name":"Scarcity","score":0.4440000057220459},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4212000072002411},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3977999985218048}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7511000037193298},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.546999990940094},{"id":"https://openalex.org/C58874564","wikidata":"https://www.wikidata.org/wiki/Q130768","display_name":"Smoke","level":2,"score":0.4948999881744385},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.48570001125335693},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.4440000057220459},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4027000069618225},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3977999985218048},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3596999943256378},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.3531999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33799999952316284},{"id":"https://openalex.org/C158016649","wikidata":"https://www.wikidata.org/wiki/Q161726","display_name":"Multinational corporation","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.2892000079154968},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.2800000011920929},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.26179999113082886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.260699987411499},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2513999938964844}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.23542","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23542","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.23542","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.23542","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Wildfires":[0],"are":[1,61,69],"an":[2,140],"escalating":[3],"global":[4],"concern":[5],"due":[6],"to":[7,102],"the":[8,12,23,28,33,49,104,131,137],"devastating":[9],"impacts":[10],"on":[11,78],"environment,":[13],"economy,":[14],"and":[15,27,66,75,85,117,156],"human":[16],"health,":[17],"with":[18,130],"notable":[19],"incidents":[20],"such":[21],"as":[22,44],"2019-2020":[24],"Australian":[25,134],"bushfires":[26],"2025":[29],"California":[30],"wildfires":[31],"underscoring":[32],"severity":[34],"of":[35,52,142],"these":[36,89],"events.":[37],"AI-enabled":[38],"camera-based":[39],"smoke":[40,57,96,150],"detection":[41,51,65],"has":[42],"emerged":[43],"a":[45,94,113],"promising":[46],"approach":[47],"for":[48,63],"rapid":[50],"wildfires.":[53],"However,":[54],"existing":[55],"wildfire":[56],"segmentation":[58,67,97,151],"datasets":[59,129],"that":[60,124],"used":[62],"training":[64,84],"models":[68],"limited":[70],"in":[71,107],"scale,":[72],"geographically":[73,115],"constrained,":[74],"often":[76],"rely":[77],"synthetic":[79],"imagery,":[80,135],"which":[81],"hinders":[82],"effective":[83],"generalization.":[86],"To":[87],"overcome":[88],"limitations,":[90],"we":[91,111,148],"present":[92],"AusSmoke,":[93],"new":[95],"dataset":[98],"collected":[99,133],"from":[100],"Australia":[101],"address":[103],"data":[105],"scarcity":[106],"this":[108],"region.":[109],"Furthermore,":[110],"introduce":[112],"MultiNational":[114],"diverse":[116,160],"substantially":[118],"larger":[119],"fully-labelled":[120],"benchmark,":[121],"called":[122],"MultiNatSmoke,":[123],"consolidates":[125],"publicly":[126],"available":[127,166],"international":[128],"newly":[132],"expanding":[136],"scale":[138],"by":[139],"order":[141],"magnitude":[143],"over":[144],"previous":[145],"collections.":[146],"Finally,":[147],"benchmark":[149],"models,":[152],"demonstrating":[153],"improved":[154],"performance":[155],"enhanced":[157],"generalization":[158],"across":[159],"geographical":[161],"contexts.":[162],"The":[163],"project":[164],"is":[165],"at":[167],"\\href{https://github.com/henryzhao0615/MultiNatSmoke}{Github}.":[168]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-29T00:00:00"}
