{"id":"https://openalex.org/W4389109101","doi":"https://doi.org/10.1145/3628454.3631198","title":"A Modified Snake Optimizer Algorithm with Otsu-based Method for Satellite Image Segmentation","display_name":"A Modified Snake Optimizer Algorithm with Otsu-based Method for Satellite Image Segmentation","publication_year":2023,"publication_date":"2023-11-28","ids":{"openalex":"https://openalex.org/W4389109101","doi":"https://doi.org/10.1145/3628454.3631198"},"language":"en","primary_location":{"id":"doi:10.1145/3628454.3631198","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3628454.3631198","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3628454.3631198","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Advances in Information Technology","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3628454.3631198","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiahao Fu","orcid":"https://orcid.org/0009-0001-1767-7937"},"institutions":[{"id":"https://openalex.org/I115748381","display_name":"Assumption University","ror":"https://ror.org/03zmqc707","country_code":"TH","type":"education","lineage":["https://openalex.org/I115748381"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Jiahao Fu","raw_affiliation_strings":["Computer Science, Assumption University, Thailand"],"raw_orcid":"https://orcid.org/0009-0001-1767-7937","affiliations":[{"raw_affiliation_string":"Computer Science, Assumption University, Thailand","institution_ids":["https://openalex.org/I115748381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060109660","display_name":"Rachsuda Setthawong","orcid":"https://orcid.org/0009-0005-0666-3547"},"institutions":[{"id":"https://openalex.org/I115748381","display_name":"Assumption University","ror":"https://ror.org/03zmqc707","country_code":"TH","type":"education","lineage":["https://openalex.org/I115748381"]}],"countries":["TH"],"is_corresponding":false,"raw_author_name":"Rachsuda Setthawong","raw_affiliation_strings":["Computer Science, Assumption University, Thailand"],"raw_orcid":"https://orcid.org/0009-0005-0666-3547","affiliations":[{"raw_affiliation_string":"Computer Science, Assumption University, Thailand","institution_ids":["https://openalex.org/I115748381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I115748381"],"apc_list":null,"apc_paid":null,"fwci":0.9186,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.83534592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9976999759674072,"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"}},"topics":[{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9976999759674072,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9959999918937683,"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/T13282","display_name":"Automated Road and Building Extraction","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/otsus-method","display_name":"Otsu's method","score":0.8166698217391968},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.7083653211593628},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.704977810382843},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6423003673553467},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6016232371330261},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5591198205947876},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5076147317886353},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.5037340521812439},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4445139169692993},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.43629151582717896},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4161131978034973},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3806438446044922},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35031265020370483},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12276259064674377}],"concepts":[{"id":"https://openalex.org/C21729346","wikidata":"https://www.wikidata.org/wiki/Q2444417","display_name":"Otsu's method","level":4,"score":0.8166698217391968},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.7083653211593628},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.704977810382843},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6423003673553467},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6016232371330261},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5591198205947876},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5076147317886353},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.5037340521812439},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4445139169692993},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.43629151582717896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4161131978034973},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3806438446044922},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35031265020370483},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12276259064674377},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3628454.3631198","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3628454.3631198","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3628454.3631198","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Advances in Information Technology","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3628454.3631198","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3628454.3631198","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3628454.3631198","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th International Conference on Advances in Information Technology","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389109101.pdf","grobid_xml":"https://content.openalex.org/works/W4389109101.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1991927948","https://openalex.org/W2008748102","https://openalex.org/W2027091505","https://openalex.org/W2062406763","https://openalex.org/W2070350630","https://openalex.org/W2071469153","https://openalex.org/W2079529529","https://openalex.org/W2083970667","https://openalex.org/W2133059825","https://openalex.org/W2895863033","https://openalex.org/W2899007243","https://openalex.org/W2945267757","https://openalex.org/W3000280880","https://openalex.org/W3132455321","https://openalex.org/W4212993228","https://openalex.org/W4223433849","https://openalex.org/W4295177766","https://openalex.org/W4306887979"],"related_works":["https://openalex.org/W4309330417","https://openalex.org/W1497460680","https://openalex.org/W2061057206","https://openalex.org/W2219579304","https://openalex.org/W3095400015","https://openalex.org/W2147223569","https://openalex.org/W2380810282","https://openalex.org/W2054831422","https://openalex.org/W4389779685","https://openalex.org/W2327601824"],"abstract_inverted_index":{"Image":[0],"segmentation":[1,141],"is":[2,31,60,89],"an":[3,17],"important":[4],"step":[5],"in":[6,16,97,110,120,140],"image":[7,18],"analysis":[8],"that":[9,36,116],"aims":[10],"to":[11,23,40,128],"segment":[12,41],"regions":[13,42],"of":[14,52,107],"interest":[15],"by":[19,43],"assigning":[20],"a":[21,32,38,67],"label":[22],"individual":[24],"pixels":[25],"sharing":[26],"certain":[27],"characteristics.":[28],"Otsu-based":[29,138],"method":[30,95,139],"well-known":[33],"thresholding":[34],"technique":[35],"selects":[37],"threshold":[39,94],"maximizing":[44],"the":[45,85,92,104,117,123,132,136],"variance":[46],"between":[47],"classes.":[48],"Despite":[49],"its":[50,57],"advantages":[51],"considerable":[53],"effectiveness":[54],"and":[55,76,131,143],"stability,":[56],"major":[58],"drawback":[59],"high":[61],"computational":[62],"cost.":[63],"This":[64],"paper":[65],"proposes":[66],"Modified":[68],"Snake":[69,79],"Optimizer":[70,80],"algorithm":[71],"(MSO),":[72],"which":[73,101],"can":[74],"dynamically":[75],"efficiently":[77],"tune":[78],"(SO)":[81],"parameters.":[82],"To":[83],"address":[84],"aforementioned":[86],"drawback,":[87],"MSO":[88],"applied":[90],"with":[91],"Otsu":[93],"(MSO-Otsu)":[96],"segmenting":[98],"satellite":[99],"images":[100],"helps":[102],"analyze":[103],"snow-covered":[105],"areas":[106],"mountain":[108],"ranges":[109],"China.":[111],"The":[112],"experimental":[113],"results":[114,142],"show":[115],"proposed":[118,133],"MSO,":[119],"general,":[121],"outperformed":[122],"traditional":[124,137],"SO":[125],"when":[126],"applying":[127],"benchmark":[129],"functions,":[130],"MSO-Otsu":[134],"outperforms":[135],"convergence":[144],"time.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-08-25T07:29:55.448023","created_date":"2025-10-10T00:00:00"}
