{"id":"https://openalex.org/W2971172687","doi":"https://doi.org/10.1109/icip.2019.8803169","title":"Learning Iteration-Dependent Denoisers for Model-Consistent Compressive Sensing","display_name":"Learning Iteration-Dependent Denoisers for Model-Consistent Compressive Sensing","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2971172687","doi":"https://doi.org/10.1109/icip.2019.8803169","mag":"2971172687"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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/A5007086799","display_name":"Pavan Kumar Reddy K","orcid":"https://orcid.org/0000-0002-2800-8755"},"institutions":[{"id":"https://openalex.org/I55215948","display_name":"Tata Consultancy Services (India)","ror":"https://ror.org/01b9n8m42","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210086519","https://openalex.org/I55215948"]},{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Pavan Kumar Reddy K.","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Science, Bengaluru, India","Indian Institute of Science, Bengaluru, India","TCS Research and Innovation, Tata Consultancy Services, Bengaluru, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Science, Bengaluru, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"Indian Institute of Science, Bengaluru, India","institution_ids":["https://openalex.org/I59270414"]},{"raw_affiliation_string":"TCS Research and Innovation, Tata Consultancy Services, Bengaluru, India","institution_ids":["https://openalex.org/I55215948"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045035201","display_name":"Kunal N. Chaudhury","orcid":"https://orcid.org/0000-0002-8136-605X"},"institutions":[{"id":"https://openalex.org/I59270414","display_name":"Indian Institute of Science Bangalore","ror":"https://ror.org/04dese585","country_code":"IN","type":"education","lineage":["https://openalex.org/I59270414"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kunal N. Chaudhury","raw_affiliation_strings":["Indian Institute of Science, Bangalore, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Science, Bangalore, India","institution_ids":["https://openalex.org/I59270414"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007086799"],"corresponding_institution_ids":["https://openalex.org/I55215948","https://openalex.org/I59270414"],"apc_list":null,"apc_paid":null,"fwci":0.3783,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.59174874,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"57","issue":null,"first_page":"2090","last_page":"2094"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T11739","display_name":"Microwave Imaging and Scattering Analysis","score":0.9983999729156494,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.793264627456665},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6086876392364502},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5974723100662231},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.558702290058136},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5234400629997253},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5078144669532776},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.49307820200920105},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4703904390335083},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.464346706867218},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4548001289367676},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.39908117055892944},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3899015188217163},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3490227460861206},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.1557299792766571},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08305969834327698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.793264627456665},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6086876392364502},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5974723100662231},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.558702290058136},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5234400629997253},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5078144669532776},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.49307820200920105},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4703904390335083},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.464346706867218},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4548001289367676},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39908117055892944},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3899015188217163},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3490227460861206},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.1557299792766571},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08305969834327698},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803169","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803169","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W54257720","https://openalex.org/W143004564","https://openalex.org/W1836465849","https://openalex.org/W1861492603","https://openalex.org/W1946620893","https://openalex.org/W1963882359","https://openalex.org/W2029816571","https://openalex.org/W2049502219","https://openalex.org/W2087416986","https://openalex.org/W2100556411","https://openalex.org/W2121927366","https://openalex.org/W2122548617","https://openalex.org/W2123241700","https://openalex.org/W2124964692","https://openalex.org/W2130120519","https://openalex.org/W2135780853","https://openalex.org/W2145096794","https://openalex.org/W2146337213","https://openalex.org/W2163973643","https://openalex.org/W2164278908","https://openalex.org/W2164452299","https://openalex.org/W2273561594","https://openalex.org/W2296055064","https://openalex.org/W2296616510","https://openalex.org/W2508457857","https://openalex.org/W2574952845","https://openalex.org/W2604885021","https://openalex.org/W2613155248","https://openalex.org/W2765431787","https://openalex.org/W2798559986","https://openalex.org/W2902719825","https://openalex.org/W2963676935","https://openalex.org/W3105425607","https://openalex.org/W4250955649","https://openalex.org/W4292363360","https://openalex.org/W6602211262","https://openalex.org/W6638667902","https://openalex.org/W6639102338","https://openalex.org/W6678856934","https://openalex.org/W6681686951"],"related_works":["https://openalex.org/W2158224665","https://openalex.org/W2379589510","https://openalex.org/W2810730439","https://openalex.org/W4300044672","https://openalex.org/W1881631164","https://openalex.org/W2358292267","https://openalex.org/W2978729728","https://openalex.org/W2378166785","https://openalex.org/W1964277756","https://openalex.org/W4220659530"],"abstract_inverted_index":{"Modern":[0],"regularization":[1],"techniques":[2],"and":[3,65,126],"iterative":[4,53,85],"solvers":[5,86],"have":[6,26,78],"largely":[7],"been":[8],"the":[9,12,43,49,62,81,93,114,117,141,153,157],"key":[10],"to":[11,40,69,109,128,136,164],"success":[13],"of":[14,33,61,83],"Compressive":[15],"Sensing":[16],"(CS).":[17],"Recently,":[18],"deep":[19],"neural":[20],"networks":[21],"(DNNs)":[22],"with":[23,48,99,169],"end-to-end":[24],"training":[25],"shown":[27,79],"promise":[28],"for":[29],"CS.":[30],"However,":[31],"because":[32],"their":[34],"open-ended":[35],"nature,":[36],"it":[37],"is":[38,46,123],"difficult":[39,127],"ensure":[41],"that":[42,80,116,149],"DNN":[44,101],"output":[45],"consistent":[47],"measurements.":[50],"In":[51],"contrast,":[52],"algorithms":[54],"such":[55],"as":[56,172],"FISTA":[57,142],"explicitly":[58],"make":[59],"use":[60,137],"measurement":[63,176],"model":[64],"are":[66,106,162],"hence":[67],"able":[68,163],"incorporate":[70],"consistency.":[71,177],"To":[72],"strike":[73],"a":[74],"middle":[75],"path,":[76],"researchers":[77],"performance":[82],"traditional":[84],"can":[87,150],"be":[88],"improved":[89],"by":[90,131],"formally":[91],"replacing":[92],"proximal":[94],"map":[95],"at":[96],"each":[97,121],"iteration":[98,122],"powerful":[100],"denoisers.":[102],"While":[103],"existing":[104],"denoisers":[105,139],"typically":[107],"designed":[108],"handle":[110,152],"additive":[111],"white":[112],"noise,":[113],"noise":[115,154],"denoiser":[118],"encounters":[119],"during":[120],"highly":[124],"correlated":[125],"characterize.":[129],"Motivated":[130],"this":[132],"observation,":[133],"we":[134,145],"propose":[135],"iteration-dependent":[138],"within":[140],"framework,":[143],"i.e.,":[144],"train":[146],"separate":[147],"DNNs":[148],"specifically":[151],"encountered":[155],"in":[156],"first":[158],"few":[159],"iterations.":[160],"We":[161],"achieve":[165],"state-of-the-art":[166],"CS":[167],"results":[168],"fewer":[170],"iterations":[171],"result,":[173],"while":[174],"maintaining":[175]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
