{"id":"https://openalex.org/W2900139389","doi":"https://doi.org/10.1109/lsp.2018.2879184","title":"PhaseNet: A Deep Convolutional Neural Network for Two-Dimensional Phase Unwrapping","display_name":"PhaseNet: A Deep Convolutional Neural Network for Two-Dimensional Phase Unwrapping","publication_year":2018,"publication_date":"2018-11-06","ids":{"openalex":"https://openalex.org/W2900139389","doi":"https://doi.org/10.1109/lsp.2018.2879184","mag":"2900139389"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2018.2879184","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"journal-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/A5000676745","display_name":"G. E. Spoorthi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210109292","display_name":"Indian Institute of Technology Tirupati","ror":"https://ror.org/01xtkxh20","country_code":"IN","type":"funder","lineage":["https://openalex.org/I4210109292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"G. E. Spoorthi","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India","institution_ids":["https://openalex.org/I4210109292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001231357","display_name":"Subrahmanyam Gorthi","orcid":"https://orcid.org/0000-0003-1957-6985"},"institutions":[{"id":"https://openalex.org/I4210109292","display_name":"Indian Institute of Technology Tirupati","ror":"https://ror.org/01xtkxh20","country_code":"IN","type":"funder","lineage":["https://openalex.org/I4210109292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Subrahmanyam Gorthi","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India","institution_ids":["https://openalex.org/I4210109292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014702481","display_name":"Rama Krishna Gorthi","orcid":"https://orcid.org/0000-0001-5021-0071"},"institutions":[{"id":"https://openalex.org/I4210109292","display_name":"Indian Institute of Technology Tirupati","ror":"https://ror.org/01xtkxh20","country_code":"IN","type":"funder","lineage":["https://openalex.org/I4210109292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Rama Krishna Sai Subrahmanyam Gorthi","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology Tirupati, Tirupati, India","institution_ids":["https://openalex.org/I4210109292"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.085,"has_fulltext":true,"fulltext_origin":"ngrams","cited_by_count":209,"citation_normalized_percentile":{"value":0.899044,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"26","issue":"1","first_page":"54","last_page":"58"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9999,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9999,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9974,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9961,"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"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83343107},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.70967054},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7020914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.63873667},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5289165},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.46581793},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.44831964},{"id":"https://openalex.org/C44280652","wikidata":"https://www.wikidata.org/wiki/Q104837","display_name":"Phase (matter)","level":2,"score":0.43368983},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41723648},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4169798},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.29789105},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2018.2879184","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_indexed_in_scopus":true,"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":null,"is_accepted":false,"is_published":false}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.43,"display_name":"Industry, innovation and infrastructure"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":26,"referenced_works":["https://openalex.org/W1533162639","https://openalex.org/W1677182931","https://openalex.org/W1836465849","https://openalex.org/W1885185971","https://openalex.org/W1894563927","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1905829557","https://openalex.org/W2096101715","https://openalex.org/W2126254938","https://openalex.org/W2131147191","https://openalex.org/W2152403125","https://openalex.org/W2155541015","https://openalex.org/W2159006012","https://openalex.org/W2172106436","https://openalex.org/W2299272558","https://openalex.org/W2325708443","https://openalex.org/W2563705555","https://openalex.org/W2587221109","https://openalex.org/W2789955947","https://openalex.org/W2807495038","https://openalex.org/W2963446712","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W4294375521","https://openalex.org/W585975565"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W4312417841","https://openalex.org/W4293226380","https://openalex.org/W4226493464","https://openalex.org/W3193565141","https://openalex.org/W3167935049","https://openalex.org/W3133861977","https://openalex.org/W3103566983","https://openalex.org/W3029198973","https://openalex.org/W2085033728"],"abstract_inverted_index":{"Phase":[0],"unwrapping":[1,30,146,211],"is":[2,70,105,163],"a":[3,26,73,86,92,203],"crucial":[4],"signal":[5],"processing":[6],"problem":[7,45],"in":[8,107,123,131],"several":[9,113],"applications":[10],"that":[11,177],"aims":[12],"to":[13,165,168],"restore":[14],"original":[15,51],"phase":[16,32,52,101,125,145,188,210],"from":[17],"the":[18,31,44,55,99,103,118,132,137,141,151,191,197,200],"wrapped":[19,124],"phase.":[20],"In":[21],"this":[22,69],"letter,":[23],"we":[24],"propose":[25],"novel":[27],"framework":[28,139,162,193],"for":[29,156,187,199],"using":[33],"deep":[34,75,178,207],"fully":[35],"convolutional":[36,179],"neural":[37,180],"network":[38,89,119,181],"termed":[39],"as":[40,53],"PhaseNet.":[41],"We":[42,135],"reformulate":[43],"definition":[46],"of":[47,59,82,112,202,206],"directly":[48],"obtaining":[49,54],"continuous":[50],"wrap-count":[56,104],"(integer":[57],"jump":[58],"2":[60],"\u03c0)":[61],"at":[62],"each":[63],"pixel":[64],"by":[65,91],"semantic":[66],"segmentation":[67],"and":[68,102,148,170,190],"accomplished":[71],"through":[72],"suitable":[74],"learning":[76,121,208],"framework.":[77],"The":[78,96,160,173],"proposed":[79,138,161,192],"architecture":[80],"consists":[81],"an":[83],"encoder":[84],"network,":[85],"corresponding":[87],"decoder":[88],"followed":[90],"pixel-wise":[93],"classification":[94],"layer.":[95],"relationship":[97],"between":[98],"absolute":[100],"leveraged":[106],"generating":[108],"abundant":[109],"simulated":[110],"data":[111],"random":[114],"shapes.":[115],"This":[116],"deliberates":[117],"on":[120],"continuity":[122],"maps":[126],"rather":[127],"than":[128],"specific":[129],"patterns":[130],"training":[133],"data.":[134],"compare":[136],"with":[140,150],"widely":[142],"adapted":[143],"quality-guided":[144],"algorithm":[147],"also":[149],"well-known":[152],"MATLAB's":[153],"unwrap":[154],"function":[155],"varying":[157],"noise":[158,169],"levels.":[159],"found":[164],"be":[166,184],"robust":[167],"computationally":[171],"fast.":[172],"results":[174],"obtained":[175],"highlight":[176],"can":[182],"indeed":[183],"effectively":[185],"applied":[186],"unwrapping,":[189],"will":[194],"hopefully":[195],"pave":[196],"way":[198],"development":[201],"new":[204],"set":[205],"based":[209],"methods.":[212]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W2900139389","counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":33},{"year":2023,"cited_by_count":58},{"year":2022,"cited_by_count":46},{"year":2021,"cited_by_count":40},{"year":2020,"cited_by_count":19},{"year":2019,"cited_by_count":8}],"updated_date":"2025-04-23T03:50:23.835496","created_date":"2018-11-16"}