{"id":"https://openalex.org/W4402261063","doi":"https://doi.org/10.1109/igarss53475.2024.10641142","title":"Application-Specific Synthetic Aperture Radar Image Clustering with Convolutional Autoencoders on Example of Sentinel-1 Scenes Acquired Over Sea Ice","display_name":"Application-Specific Synthetic Aperture Radar Image Clustering with Convolutional Autoencoders on Example of Sentinel-1 Scenes Acquired Over Sea Ice","publication_year":2024,"publication_date":"2024-07-07","ids":{"openalex":"https://openalex.org/W4402261063","doi":"https://doi.org/10.1109/igarss53475.2024.10641142"},"language":"en","primary_location":{"id":"doi:10.1109/igarss53475.2024.10641142","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","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/A5004572569","display_name":"Dmitrii Murashkin","orcid":"https://orcid.org/0000-0002-5818-0038"},"institutions":[{"id":"https://openalex.org/I2898391981","display_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","ror":"https://ror.org/04bwf3e34","country_code":"DE","type":"facility","lineage":["https://openalex.org/I1305996414","https://openalex.org/I2898391981"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Dmitrii Murashkin","raw_affiliation_strings":["Remote Sensing Technology Institute,German Aerospace Center (DLR),Bremen"],"affiliations":[{"raw_affiliation_string":"Remote Sensing Technology Institute,German Aerospace Center (DLR),Bremen","institution_ids":["https://openalex.org/I2898391981"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5004572569"],"corresponding_institution_ids":["https://openalex.org/I2898391981"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18189138,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"11","issue":null,"first_page":"96","last_page":"101"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11459","display_name":"Arctic and Antarctic ice dynamics","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11459","display_name":"Arctic and Antarctic ice dynamics","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14047","display_name":"Marine and environmental studies","score":0.9416999816894531,"subfield":{"id":"https://openalex.org/subfields/1910","display_name":"Oceanography"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11333","display_name":"Climate change and permafrost","score":0.9390000104904175,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.8560954928398132},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.704580545425415},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6558080315589905},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5950300097465515},{"id":"https://openalex.org/keywords/inverse-synthetic-aperture-radar","display_name":"Inverse synthetic aperture radar","score":0.5879706144332886},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5875105261802673},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.580132782459259},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5780181288719177},{"id":"https://openalex.org/keywords/side-looking-airborne-radar","display_name":"Side looking airborne radar","score":0.4439700245857239},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43570172786712646},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3505948781967163},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.3423992991447449},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.31369030475616455},{"id":"https://openalex.org/keywords/continuous-wave-radar","display_name":"Continuous-wave radar","score":0.21788257360458374},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12348034977912903}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8560954928398132},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.704580545425415},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6558080315589905},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5950300097465515},{"id":"https://openalex.org/C109094680","wikidata":"https://www.wikidata.org/wiki/Q6060432","display_name":"Inverse synthetic aperture radar","level":4,"score":0.5879706144332886},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5875105261802673},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.580132782459259},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5780181288719177},{"id":"https://openalex.org/C62282787","wikidata":"https://www.wikidata.org/wiki/Q831483","display_name":"Side looking airborne radar","level":5,"score":0.4439700245857239},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43570172786712646},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3505948781967163},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.3423992991447449},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.31369030475616455},{"id":"https://openalex.org/C59584813","wikidata":"https://www.wikidata.org/wiki/Q1029234","display_name":"Continuous-wave radar","level":4,"score":0.21788257360458374},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12348034977912903}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss53475.2024.10641142","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/igarss53475.2024.10641142","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:elib.dlr.de:204134","is_oa":false,"landing_page_url":"https://doi.org/10.1109/IGARSS53475.2024.10641142>.","pdf_url":null,"source":{"id":"https://openalex.org/S4377196266","display_name":"elib (German Aerospace Center)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2898391981","host_organization_name":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt e. V. (DLR)","host_organization_lineage":["https://openalex.org/I2898391981"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Konferenzbeitrag"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.7699999809265137,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1970590897","https://openalex.org/W1980508351","https://openalex.org/W2027649198","https://openalex.org/W2140253783","https://openalex.org/W2483236932","https://openalex.org/W2897516365","https://openalex.org/W2909282631","https://openalex.org/W2955208048","https://openalex.org/W2997574889","https://openalex.org/W3038391328","https://openalex.org/W3043617570","https://openalex.org/W3063084726","https://openalex.org/W4210920397","https://openalex.org/W4295700829","https://openalex.org/W6681096077"],"related_works":["https://openalex.org/W2112228652","https://openalex.org/W1908474219","https://openalex.org/W2545123933","https://openalex.org/W1994788526","https://openalex.org/W2041414401","https://openalex.org/W2108352898","https://openalex.org/W2612690400","https://openalex.org/W2042726296","https://openalex.org/W2160730947","https://openalex.org/W2081203575"],"abstract_inverted_index":{"Sea":[0],"ice":[1,16,20,35,74],"is":[2,28,40,75,83,101,105,114,196],"an":[3],"important":[4],"component":[5],"of":[6,32,60,78,93,142,169,209],"the":[7,12,22,26,38,46,61,76,91,121,131,138,173,179,191,201],"Arctic":[8,27,39],"climate":[9],"system.":[10],"With":[11],"decrease":[13],"in":[14,25,37,63,130,137,190],"sea":[15,19,34,73,216],"extend":[17],"and":[18,53,134,147,185,205],"thickness,":[21],"human":[23],"activity":[24],"increasing.":[29],"Better":[30],"knowledge":[31],"present":[33],"conditions":[36],"required":[41],"for":[42,45,51,68],"better":[43],"planning":[44],"activities":[47],"as":[48,50],"well":[49],"safer":[52],"more":[54],"fuel-efficient":[55],"shipping":[56],"routes":[57],"calculation.":[58],"One":[59],"bottlenecks":[62],"semantic":[64],"segmentation":[65],"algorithm":[66,100,104],"developments":[67],"satellite":[69],"image":[70],"analysis":[71],"over":[72,215],"lack":[77],"ground":[79],"truth":[80],"information,":[81],"which":[82,113],"often":[84],"very":[85],"hard":[86],"to":[87,116,120],"acquire.":[88],"To":[89],"tackle":[90],"problem":[92],"limited":[94],"labeled":[95,212],"data,":[96],"a":[97,108,206],"semi-supervised":[98],"clustering":[99,195],"suggested.":[102],"The":[103,194],"based":[106,199],"on":[107,155,200],"convolutional":[109],"neural":[110],"network":[111],"autoencoder,":[112],"able":[115],"learn":[117],"descriptors":[118,204],"specific":[119],"application.":[122],"Four":[123],"autoencoders":[124,171],"are":[125,153,176],"trained":[126,154],"with":[127,157,164,181],"998":[128],"scenes":[129,136],"training":[132,192],"dataset":[133],"222":[135],"test":[139],"dataset.":[140,193],"Two":[141,151],"them":[143],"include":[144],"batch":[145,182],"normalization":[146,183],"two":[148,162],"do":[149],"not.":[150],"autoencoder":[152,180],"data":[156],"open":[158,165,186],"ocean":[159,166,187],"masked":[160,188],"out,":[161],"-":[163],"included.":[167],"Out":[168],"four":[170],"trained,":[172],"best":[174],"results":[175],"shown":[177],"by":[178],"included":[184],"out":[189],"then":[197],"done":[198],"learned":[202],"encoder":[203],"small":[207],"set":[208],"seven":[210],"manually":[211],"images":[213],"acquired":[214],"ice.":[217]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2024-09-06T00:00:00"}