{"id":"https://openalex.org/W3035463184","doi":"https://doi.org/10.1109/saci46893.2019.9111474","title":"Lunar Crater Detection based on Grid Partition using Deep Learning","display_name":"Lunar Crater Detection based on Grid Partition using Deep Learning","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W3035463184","doi":"https://doi.org/10.1109/saci46893.2019.9111474","mag":"3035463184"},"language":"en","primary_location":{"id":"doi:10.1109/saci46893.2019.9111474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/saci46893.2019.9111474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI)","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/A5047247886","display_name":"Shintaro Hashimoto","orcid":"https://orcid.org/0000-0001-8674-8156"},"institutions":[{"id":"https://openalex.org/I2800865746","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800865746"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Shintaro Hashimoto","raw_affiliation_strings":["Research Unit III, Reserach and Development Directorate Japan Aerospace Exploration Agency (JAXA) 2-1-1 Sengen, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"Research Unit III, Reserach and Development Directorate Japan Aerospace Exploration Agency (JAXA) 2-1-1 Sengen, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I2800865746"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109004705","display_name":"Kenji Mori","orcid":null},"institutions":[{"id":"https://openalex.org/I2800865746","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800865746"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kenji Mori","raw_affiliation_strings":["Research Unit III, Reserach and Development Directorate Japan Aerospace Exploration Agency (JAXA) 2-1-1 Sengen, Tsukuba, Ibaraki, Japan"],"affiliations":[{"raw_affiliation_string":"Research Unit III, Reserach and Development Directorate Japan Aerospace Exploration Agency (JAXA) 2-1-1 Sengen, Tsukuba, Ibaraki, Japan","institution_ids":["https://openalex.org/I2800865746"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5047247886"],"corresponding_institution_ids":["https://openalex.org/I2800865746"],"apc_list":null,"apc_paid":null,"fwci":0.4729,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.71344212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"75","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10406","display_name":"Planetary Science and Exploration","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10406","display_name":"Planetary Science and Exploration","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9726999998092651,"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/T10325","display_name":"Astro and Planetary Science","score":0.9358000159263611,"subfield":{"id":"https://openalex.org/subfields/3103","display_name":"Astronomy and Astrophysics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/impact-crater","display_name":"Impact crater","score":0.9652791023254395},{"id":"https://openalex.org/keywords/orbiter","display_name":"Orbiter","score":0.7347471117973328},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.5462732315063477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5412800312042236},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5348464846611023},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5252834558486938},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.49410298466682434},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4821469485759735},{"id":"https://openalex.org/keywords/digital-elevation-model","display_name":"Digital elevation model","score":0.4369436800479889},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.43351393938064575},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4112223982810974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38720259070396423},{"id":"https://openalex.org/keywords/geodesy","display_name":"Geodesy","score":0.30198585987091064},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08285760879516602},{"id":"https://openalex.org/keywords/astrobiology","display_name":"Astrobiology","score":0.07427653670310974}],"concepts":[{"id":"https://openalex.org/C179537507","wikidata":"https://www.wikidata.org/wiki/Q55818","display_name":"Impact crater","level":2,"score":0.9652791023254395},{"id":"https://openalex.org/C2776481522","wikidata":"https://www.wikidata.org/wiki/Q40218","display_name":"Orbiter","level":2,"score":0.7347471117973328},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.5462732315063477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5412800312042236},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5348464846611023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5252834558486938},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.49410298466682434},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4821469485759735},{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.4369436800479889},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.43351393938064575},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4112223982810974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38720259070396423},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.30198585987091064},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08285760879516602},{"id":"https://openalex.org/C87355193","wikidata":"https://www.wikidata.org/wiki/Q411","display_name":"Astrobiology","level":1,"score":0.07427653670310974},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/saci46893.2019.9111474","is_oa":false,"landing_page_url":"https://doi.org/10.1109/saci46893.2019.9111474","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 13th International Symposium on Applied Computational Intelligence and Informatics (SACI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1998899726","https://openalex.org/W2070651968","https://openalex.org/W2087807155","https://openalex.org/W2094194826","https://openalex.org/W2792008101","https://openalex.org/W2796347433","https://openalex.org/W2864198995","https://openalex.org/W2963073614","https://openalex.org/W4293584584","https://openalex.org/W6729966448","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W2625809971","https://openalex.org/W1663847441","https://openalex.org/W2768493687","https://openalex.org/W2170886505","https://openalex.org/W1969484083","https://openalex.org/W2743845306","https://openalex.org/W2792375831","https://openalex.org/W2386713424","https://openalex.org/W3170601672","https://openalex.org/W1663871082"],"abstract_inverted_index":{"Although":[0],"a":[1,28,59,101,133,137],"digital":[2],"elevation":[3],"model":[4],"(DEM)":[5],"is":[6],"often":[7],"used":[8],"for":[9,64],"crater":[10,30,65,111,124],"classification,":[11],"the":[12,35,42,47,70,93,107],"DEM":[13],"has":[14],"low":[15],"resolution":[16,53],"and":[17,105,140,147,153],"thus":[18],"may":[19],"not":[20,73],"reveal":[21],"small":[22,29],"craters.":[23],"This":[24,56],"research":[25,57],"showed":[26],"that":[27],"found":[31],"in":[32,112,128],"images":[33,94],"of":[34,46,72,109],"lunar":[36],"south":[37],"pole":[38],"region,":[39],"taken":[40],"by":[41,91],"Narrow":[43],"Angle":[44],"Camera":[45],"Lunar":[48],"Reconnaissance":[49],"Orbiter,":[50],"had":[51,69],"higher":[52],"than":[54],"DEM.":[55],"adopted":[58],"convolutional":[60],"neural":[61],"network":[62],"(CNN)":[63],"classification.":[66],"However,":[67],"CNN":[68],"problem":[71],"being":[74],"able":[75],"to":[76,83],"classify":[77,122],"multiple":[78],"craters":[79],"at":[80],"once":[81],"due":[82],"its":[84],"fixed":[85],"length":[86],"output.":[87],"In":[88],"this":[89],"research,":[90],"dividing":[92],"into":[95],"grids,":[96],"equaling":[97],"output":[98],"size/input":[99],"using":[100,115],"semantic":[102],"segmentation":[103],"technique,":[104,119],"detecting":[106],"position":[108],"each":[110,113,123],"grid":[114],"an":[116],"object":[117],"detection":[118],"we":[120],"could":[121],"even":[125],"if":[126],"appearing":[127],"only":[129],"one":[130],"pixel":[131],"from":[132],"large":[134],"image":[135],"with":[136],"numerical":[138],"value":[139],"high":[141],"accuracy":[142],"rate.":[143],"The":[144],"recall":[145],"rate":[146,150],"maximum":[148],"precision":[149],"was":[151],"80.5%":[152],"77.3%":[154],"respectively.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}