{"id":"https://openalex.org/W3132083182","doi":"https://doi.org/10.1109/igarss39084.2020.9324490","title":"Visualization of Deep Transfer Learning in SAR Imagery","display_name":"Visualization of Deep Transfer Learning in SAR Imagery","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3132083182","doi":"https://doi.org/10.1109/igarss39084.2020.9324490","mag":"3132083182"},"language":"en","primary_location":{"id":"doi:10.1109/igarss39084.2020.9324490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324490","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.11061","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044494955","display_name":"Abu Md Niamul Taufique","orcid":"https://orcid.org/0000-0001-7895-7679"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abu Md Niamul Taufique","raw_affiliation_strings":["Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067832911","display_name":"Navya Nagananda","orcid":"https://orcid.org/0000-0002-9963-5836"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Navya Nagananda","raw_affiliation_strings":["Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5022041853","display_name":"Andreas Savakis","orcid":"https://orcid.org/0000-0002-9657-3027"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Andreas Savakis","raw_affiliation_strings":["Rochester Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rochester Institute of Technology","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155173764"],"apc_list":null,"apc_paid":null,"fwci":0.46,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.67307245,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"3497","last_page":"3500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11038","display_name":"Advanced SAR Imaging Techniques","score":0.9940000176429749,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9868000149726868,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/synthetic-aperture-radar","display_name":"Synthetic aperture radar","score":0.8612841367721558},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7844983339309692},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7582918405532837},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7034963369369507},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6256161332130432},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6139031648635864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6074700951576233},{"id":"https://openalex.org/keywords/radar-imaging","display_name":"Radar imaging","score":0.5405721664428711},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3988458514213562},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3509499430656433},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.34174835681915283},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.14253348112106323},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.08288460969924927}],"concepts":[{"id":"https://openalex.org/C87360688","wikidata":"https://www.wikidata.org/wiki/Q740686","display_name":"Synthetic aperture radar","level":2,"score":0.8612841367721558},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7844983339309692},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7582918405532837},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7034963369369507},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6256161332130432},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6139031648635864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6074700951576233},{"id":"https://openalex.org/C10929652","wikidata":"https://www.wikidata.org/wiki/Q7279985","display_name":"Radar imaging","level":3,"score":0.5405721664428711},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3988458514213562},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3509499430656433},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.34174835681915283},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.14253348112106323},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.08288460969924927}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/igarss39084.2020.9324490","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss39084.2020.9324490","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.11061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.11061","pdf_url":"https://arxiv.org/pdf/2103.11061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.11061","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.11061","pdf_url":"https://arxiv.org/pdf/2103.11061","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Life below water","score":0.8500000238418579,"id":"https://metadata.un.org/sdg/14"}],"awards":[{"id":"https://openalex.org/G959409320","display_name":null,"funder_award_id":"FA9550-18-1-0121","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2161381512","https://openalex.org/W2163605009","https://openalex.org/W2547578938","https://openalex.org/W2889198848","https://openalex.org/W2944029760","https://openalex.org/W2962858109","https://openalex.org/W2964121744","https://openalex.org/W3102564565","https://openalex.org/W3122279293","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2545123933","https://openalex.org/W2585813813","https://openalex.org/W2042726296","https://openalex.org/W2096748030","https://openalex.org/W3016428515","https://openalex.org/W2160730947","https://openalex.org/W2747205507","https://openalex.org/W2917196883","https://openalex.org/W1908997176","https://openalex.org/W2081203575"],"abstract_inverted_index":{"Synthetic":[0],"Aperture":[1],"Radar":[2],"(SAR)":[3],"imagery":[4,108],"has":[5],"diverse":[6],"applications":[7],"in":[8,29,93],"land":[9],"and":[10,25,32,81,109],"marine":[11],"surveillance.":[12],"Unlike":[13],"electro-optical":[14],"(EO)":[15],"systems,":[16],"these":[17],"systems":[18],"are":[19],"not":[20],"affected":[21],"by":[22,88],"weather":[23],"conditions":[24],"can":[26,54],"be":[27,44,56],"used":[28,57],"the":[30,36,90,94,102],"day":[31],"night":[33],"times.":[34],"With":[35],"growing":[37],"importance":[38],"of":[39,96],"SAR":[40,59,85,107],"imagery,":[41],"it":[42],"would":[43],"desirable":[45],"if":[46],"models":[47],"trained":[48,75],"on":[49,76,84,112],"widely":[50],"available":[51],"EO":[52,78],"datasets":[53],"also":[55],"for":[58],"images.":[60],"In":[61],"this":[62],"work,":[63],"we":[64,100],"consider":[65],"transfer":[66,103],"learning":[67,104],"to":[68,106],"leverage":[69],"deep":[70,115],"features":[71],"from":[72],"a":[73,114,118],"network":[74,91,116],"an":[77],"ships":[79],"dataset":[80],"generate":[82],"predictions":[83],"imagery.":[86],"Furthermore,":[87],"exploring":[89],"activations":[92],"form":[95],"class-activation":[97],"maps":[98],"(CAMs),":[99],"visualize":[101],"process":[105],"gain":[110],"insight":[111],"how":[113],"interprets":[117],"new":[119],"modality.":[120]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}