{"id":"https://openalex.org/W4416250545","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227269","title":"CS-YOLO: A cross-scale model designed for impact crater detection in Mars remote sensing images","display_name":"CS-YOLO: A cross-scale model designed for impact crater detection in Mars remote sensing images","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250545","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227269"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5017494483","display_name":"Hongguang Xiao","orcid":"https://orcid.org/0000-0002-9697-6678"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"HongGuang Xiao","raw_affiliation_strings":["Changsha University of Science & Technology,School of Computer Science,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changsha University of Science & Technology,School of Computer Science,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031715085","display_name":"S. Y. Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"ShanHua Lin","raw_affiliation_strings":["Changsha University of Science & Technology,School of Computer Science,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changsha University of Science & Technology,School of Computer Science,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067530491","display_name":"Lifu Chen","orcid":"https://orcid.org/0000-0002-7788-7987"},"institutions":[{"id":"https://openalex.org/I56934997","display_name":"Changsha University of Science and Technology","ror":"https://ror.org/03yph8055","country_code":"CN","type":"education","lineage":["https://openalex.org/I56934997"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifu Chen","raw_affiliation_strings":["Changsha University of Science & Technology,School of Electrical Engineering,Changsha,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changsha University of Science & Technology,School of Electrical Engineering,Changsha,China","institution_ids":["https://openalex.org/I56934997"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I56934997"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20566889,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10406","display_name":"Planetary Science and Exploration","score":0.9861000180244446,"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":0.9861000180244446,"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/T10325","display_name":"Astro and Planetary Science","score":0.008100000210106373,"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/T11701","display_name":"Space Satellite Systems and Control","score":0.00039999998989515007,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.6811000108718872},{"id":"https://openalex.org/keywords/impact-crater","display_name":"Impact crater","score":0.6259999871253967},{"id":"https://openalex.org/keywords/mars-exploration-program","display_name":"Mars Exploration Program","score":0.5641999840736389},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5489000082015991},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4970000088214874},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.39899998903274536},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.367000013589859}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.7688999772071838},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.6811000108718872},{"id":"https://openalex.org/C179537507","wikidata":"https://www.wikidata.org/wiki/Q55818","display_name":"Impact crater","level":2,"score":0.6259999871253967},{"id":"https://openalex.org/C83260615","wikidata":"https://www.wikidata.org/wiki/Q6773121","display_name":"Mars Exploration Program","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5489000082015991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5393999814987183},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4970000088214874},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42309999465942383},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.367000013589859},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.3346000015735626},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29499998688697815},{"id":"https://openalex.org/C2984335091","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Thermal infrared","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2660999894142151},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C183365957","wikidata":"https://www.wikidata.org/wiki/Q17140402","display_name":"Remote sensing application","level":3,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227269","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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":24,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2077882822","https://openalex.org/W2127592841","https://openalex.org/W2148848671","https://openalex.org/W2194775991","https://openalex.org/W2792008101","https://openalex.org/W3003841907","https://openalex.org/W3042011474","https://openalex.org/W3080509309","https://openalex.org/W3161978225","https://openalex.org/W3172599549","https://openalex.org/W3177954245","https://openalex.org/W3185190852","https://openalex.org/W3197022678","https://openalex.org/W3210586215","https://openalex.org/W4288759752","https://openalex.org/W4296280956","https://openalex.org/W4321498598","https://openalex.org/W4327652243","https://openalex.org/W4362703713","https://openalex.org/W4372347372","https://openalex.org/W4386076325","https://openalex.org/W4401415788","https://openalex.org/W4401976142"],"related_works":[],"abstract_inverted_index":{"Impact":[0],"crater":[1,84],"detection":[2,31,66,155,194],"based":[3,50],"on":[4,51],"remote":[5,18,164,205],"sensing":[6,19,165,206],"images":[7,20],"(RSI)":[8],"plays":[9],"a":[10,35,45,72,95,179],"key":[11,60],"role":[12],"in":[13,90,117,174,200,204],"deep":[14],"space":[15],"exploration.":[16],"However,":[17],"of":[21,32,82,108,137,182,188],"planetary":[22],"surfaces":[23],"often":[24],"suffer":[25],"from":[26],"low":[27],"resolution,":[28],"making":[29],"the":[30,52,69,80,91,105,113,121,134,147,153,168],"smaller":[33],"craters":[34,139,203],"challenging":[36],"task.":[37],"To":[38],"address":[39,79],"this":[40,42],"challenge,":[41],"paper":[43],"proposes":[44],"novel":[46],"neural":[47],"network":[48],"model":[49,70],"YOLOv7":[53],"architecture,":[54],"named":[55],"CS-YOLO.":[56],"CS-YOLO":[57,172,196],"incorporates":[58],"several":[59],"technical":[61],"innovations":[62],"to":[63,77,103,191],"enhance":[64,104],"its":[65],"performance.":[67],"First,":[68],"employs":[71],"dual-branch":[73],"downsampling":[74,89],"module":[75,99,125],"(MSDown)":[76],"effectively":[78,142],"issue":[81],"small":[83,109,138,148,176,202],"feature":[85,97,123],"attenuation":[86],"during":[87],"consecutive":[88],"backbone":[92],"network.":[93],"Second,":[94],"multi-scale":[96,129],"extraction":[98],"(MSFE)":[100],"is":[101],"designed":[102],"semantic":[106],"information":[107],"craters,":[110,177],"significantly":[111],"improving":[112,152],"model\u2019s":[114,154],"recognition":[115],"ability":[116],"complex":[118],"terrain.":[119],"Finally,":[120],"cross-scale":[122],"fusion":[124],"(CSFF)":[126],"uses":[127],"3D":[128],"convolutions,":[130],"not":[131],"only":[132],"extracting":[133],"structural":[135],"features":[136,145],"but":[140],"also":[141],"integrating":[143],"these":[144],"into":[146],"head":[149],"branch,":[150],"greatly":[151],"accuracy.Experiments":[156],"were":[157],"conducted":[158],"using":[159],"Mars":[160],"solar":[161],"thermal":[162],"infrared":[163],"images,":[166],"and":[167,184],"results":[169],"show":[170],"that":[171],"excels":[173],"detecting":[175],"achieving":[178],"recall":[180],"rate":[181,187],"82.1%":[183],"an":[185],"accuracy":[186],"86.9%.":[189],"Compared":[190],"other":[192],"object":[193],"algorithms,":[195],"demonstrates":[197],"significant":[198],"advantages":[199],"recognizing":[201],"images.":[207]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-11-14T00:00:00"}