{"id":"https://openalex.org/W2944721402","doi":"https://doi.org/10.1109/tci.2019.2915580","title":"Embedding Deep Learning in Inverse Scattering Problems","display_name":"Embedding Deep Learning in Inverse Scattering Problems","publication_year":2019,"publication_date":"2019-05-08","ids":{"openalex":"https://openalex.org/W2944721402","doi":"https://doi.org/10.1109/tci.2019.2915580","mag":"2944721402"},"language":"en","primary_location":{"id":"doi:10.1109/tci.2019.2915580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2019.2915580","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-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/A5011459316","display_name":"Yash Sanghvi","orcid":"https://orcid.org/0000-0002-7384-3573"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Yash Sanghvi","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001980735","display_name":"Yaswanth Kalepu","orcid":"https://orcid.org/0000-0002-3007-3150"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Yaswanth Kalepu","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007359654","display_name":"Uday K. Khankhoje","orcid":"https://orcid.org/0000-0002-9629-3922"},"institutions":[{"id":"https://openalex.org/I24676775","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49","country_code":"IN","type":"facility","lineage":["https://openalex.org/I24676775"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Uday K. Khankhoje","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, India","institution_ids":["https://openalex.org/I24676775"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5011459316"],"corresponding_institution_ids":["https://openalex.org/I24676775"],"apc_list":null,"apc_paid":null,"fwci":7.8354,"has_fulltext":false,"cited_by_count":149,"citation_normalized_percentile":{"value":0.9815213,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"6","issue":null,"first_page":"46","last_page":"56"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11609","display_name":"Geophysical Methods and Applications","score":0.9998000264167786,"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"}},{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.6209415197372437},{"id":"https://openalex.org/keywords/inverse-scattering-problem","display_name":"Inverse scattering problem","score":0.620207667350769},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5912559032440186},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5689734816551208},{"id":"https://openalex.org/keywords/maxima-and-minima","display_name":"Maxima and minima","score":0.5306434035301208},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.48793789744377136},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48564258217811584},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.46712902188301086},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46088147163391113},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.40616437792778015},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3837428092956543},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2277897596359253}],"concepts":[{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.6209415197372437},{"id":"https://openalex.org/C174558057","wikidata":"https://www.wikidata.org/wiki/Q11639409","display_name":"Inverse scattering problem","level":3,"score":0.620207667350769},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5912559032440186},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5689734816551208},{"id":"https://openalex.org/C186633575","wikidata":"https://www.wikidata.org/wiki/Q845060","display_name":"Maxima and minima","level":2,"score":0.5306434035301208},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.48793789744377136},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48564258217811584},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.46712902188301086},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46088147163391113},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.40616437792778015},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3837428092956543},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2277897596359253},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tci.2019.2915580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tci.2019.2915580","pdf_url":null,"source":{"id":"https://openalex.org/S4210233665","display_name":"IEEE Transactions on Computational Imaging","issn_l":"2333-9403","issn":["2333-9403","2573-0436"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Computational Imaging","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5624952945","display_name":null,"funder_award_id":"(Space Applications Centre) ECO-13","funder_id":"https://openalex.org/F4320320722","funder_display_name":"Indian Space Research Organisation"},{"id":"https://openalex.org/G5847697763","display_name":null,"funder_award_id":"ECR/2018/001953","funder_id":"https://openalex.org/F4320334771","funder_display_name":"Science and Engineering Research Board"}],"funders":[{"id":"https://openalex.org/F4320320722","display_name":"Indian Space Research Organisation","ror":"https://ror.org/00cwrns71"},{"id":"https://openalex.org/F4320322211","display_name":"Indian Institute of Technology Madras","ror":"https://ror.org/03v0r5n49"},{"id":"https://openalex.org/F4320334771","display_name":"Science and Engineering Research Board","ror":"https://ror.org/03ffdsr55"},{"id":"https://openalex.org/F4320336495","display_name":"Space Applications Centre","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1727408521","https://openalex.org/W1901129140","https://openalex.org/W1973027724","https://openalex.org/W1983275259","https://openalex.org/W1983322501","https://openalex.org/W1988483973","https://openalex.org/W1998510820","https://openalex.org/W2003147468","https://openalex.org/W2004288581","https://openalex.org/W2018446638","https://openalex.org/W2018649345","https://openalex.org/W2029460515","https://openalex.org/W2035489376","https://openalex.org/W2046094366","https://openalex.org/W2088440114","https://openalex.org/W2103662688","https://openalex.org/W2112796928","https://openalex.org/W2113481361","https://openalex.org/W2127626627","https://openalex.org/W2130129917","https://openalex.org/W2133034273","https://openalex.org/W2140277740","https://openalex.org/W2143368686","https://openalex.org/W2144559213","https://openalex.org/W2146942354","https://openalex.org/W2151980064","https://openalex.org/W2154741022","https://openalex.org/W2163605009","https://openalex.org/W2164278908","https://openalex.org/W2194775991","https://openalex.org/W2307575536","https://openalex.org/W2314254201","https://openalex.org/W2552808051","https://openalex.org/W2578009003","https://openalex.org/W2604885021","https://openalex.org/W2613155248","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2766762759","https://openalex.org/W2782977076","https://openalex.org/W2786343819","https://openalex.org/W2894120608","https://openalex.org/W2899140718","https://openalex.org/W2963037989","https://openalex.org/W2964121744","https://openalex.org/W4292363360","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6639824700"],"related_works":["https://openalex.org/W2111106738","https://openalex.org/W2970256865","https://openalex.org/W2954481250","https://openalex.org/W2128608246","https://openalex.org/W2520812953","https://openalex.org/W3101167575","https://openalex.org/W1567523647","https://openalex.org/W4321641047","https://openalex.org/W2755915683","https://openalex.org/W2144075718"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,90,140],"introduce":[4],"a":[5,41,58,118],"deep-learning-based":[6],"framework":[7,15],"to":[8,98,144],"solve":[9],"electromagnetic":[10],"inverse":[11],"scattering":[12],"problems.":[13],"This":[14],"builds":[16],"on":[17],"and":[18,37,95,153],"extends":[19],"the":[20,31,65,71,76,81,88,93,99,142],"capabilities":[21],"of":[22,43,75],"existing":[23],"physics-based":[24],"inversion":[25],"algorithms.":[26],"These":[27],"algorithms,":[28],"such":[29],"as":[30],"contrast":[32,66],"source":[33,67],"inversion,":[34],"subspace-optimization":[35],"method,":[36],"their":[38],"variants":[39],"face":[40],"problem":[42],"getting":[44],"trapped":[45],"in":[46,102,112,124,133],"false":[47],"local":[48],"minima":[49],"when":[50],"recovering":[51],"objects":[52,148],"with":[53,80],"high":[54,126,146],"permittivity.":[55],"We":[56,115],"propose":[57,117],"novel":[59,119],"convolutional":[60],"neural":[61],"network":[62],"architecture,":[63],"termed":[64],"network,":[68],"that":[69,122,149],"learns":[70],"noise":[72],"space":[73,83],"components":[74,84],"radiation":[77],"operator.":[78],"Together":[79],"signal":[82],"directly":[85],"estimated":[86],"from":[87],"data,":[89],"iteratively":[91],"refine":[92],"solution":[94,101],"show":[96],"convergence":[97],"correct":[100],"cases":[103],"where":[104],"traditional":[105],"techniques":[106],"fail":[107],"without":[108,129],"any":[109,130],"significant":[110,131],"increase":[111,132],"computational":[113,134],"time.":[114],"also":[116],"multiresolution":[120],"strategy":[121],"helps":[123],"producing":[125],"resolution":[127],"solutions":[128],"costs.":[135],"Through":[136],"extensive":[137],"numerical":[138],"experiments,":[139],"demonstrate":[141],"ability":[143],"recover":[145],"permittivity":[147],"include":[150],"homogeneous,":[151],"heterogeneous,":[152],"lossy":[154],"scatterers.":[155]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":24},{"year":2022,"cited_by_count":37},{"year":2021,"cited_by_count":26},{"year":2020,"cited_by_count":16}],"updated_date":"2026-03-14T08:43:22.919905","created_date":"2025-10-10T00:00:00"}