{"id":"https://openalex.org/W2969789619","doi":"https://doi.org/10.1109/jstsp.2021.3049634","title":"Deep Energy: Task Driven Training of Deep Neural Networks","display_name":"Deep Energy: Task Driven Training of Deep Neural Networks","publication_year":2021,"publication_date":"2021-01-07","ids":{"openalex":"https://openalex.org/W2969789619","doi":"https://doi.org/10.1109/jstsp.2021.3049634","mag":"2969789619"},"language":"en","primary_location":{"id":"doi:10.1109/jstsp.2021.3049634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3049634","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1805.12355","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073632106","display_name":"Alona Golts","orcid":"https://orcid.org/0000-0001-7103-8047"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Alona Golts","raw_affiliation_strings":["Department of Computer Science, Technion Institute of Technology, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technion Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070161627","display_name":"Daniel Z. Freedman","orcid":"https://orcid.org/0000-0001-7354-0129"},"institutions":[{"id":"https://openalex.org/I4210117425","display_name":"Google (Israel)","ror":"https://ror.org/02c20ys54","country_code":"IL","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210117425","https://openalex.org/I4210128969"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Daniel Freedman","raw_affiliation_strings":["Google Research, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Google Research, Haifa, Israel","institution_ids":["https://openalex.org/I4210117425"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020279598","display_name":"Michael Elad","orcid":"https://orcid.org/0000-0001-8131-6928"},"institutions":[{"id":"https://openalex.org/I174306211","display_name":"Technion \u2013 Israel Institute of Technology","ror":"https://ror.org/03qryx823","country_code":"IL","type":"education","lineage":["https://openalex.org/I174306211"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Michael Elad","raw_affiliation_strings":["Department of Computer Science, Technion Institute of Technology, Haifa, Israel"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Technion Institute of Technology, Haifa, Israel","institution_ids":["https://openalex.org/I174306211"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073632106"],"corresponding_institution_ids":["https://openalex.org/I174306211"],"apc_list":null,"apc_paid":null,"fwci":1.0657,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.78262068,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"15","issue":"2","first_page":"324","last_page":"338"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9976000189781189,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9952999949455261,"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":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8372988104820251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7134867906570435},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6876401901245117},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5751317739486694},{"id":"https://openalex.org/keywords/bottleneck","display_name":"Bottleneck","score":0.5263962745666504},{"id":"https://openalex.org/keywords/energy-minimization","display_name":"Energy minimization","score":0.5161717534065247},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.5022594928741455},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.47076916694641113},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46195435523986816},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.44548171758651733},{"id":"https://openalex.org/keywords/minification","display_name":"Minification","score":0.4207801818847656},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.383223295211792}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8372988104820251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7134867906570435},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6876401901245117},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5751317739486694},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.5263962745666504},{"id":"https://openalex.org/C14961307","wikidata":"https://www.wikidata.org/wiki/Q5377176","display_name":"Energy minimization","level":2,"score":0.5161717534065247},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.5022594928741455},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.47076916694641113},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46195435523986816},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.44548171758651733},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.4207801818847656},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.383223295211792},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstsp.2021.3049634","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2021.3049634","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1805.12355","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.12355","pdf_url":"https://arxiv.org/pdf/1805.12355","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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:1805.12355","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1805.12355","pdf_url":"https://arxiv.org/pdf/1805.12355","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[{"score":0.8899999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[{"id":"https://openalex.org/G7002269522","display_name":null,"funder_award_id":"335/18","funder_id":"https://openalex.org/F4320322252","funder_display_name":"Israel Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320322252","display_name":"Israel Science Foundation","ror":"https://ror.org/04sazxf24"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":106,"referenced_works":["https://openalex.org/W147243700","https://openalex.org/W611457968","https://openalex.org/W1495267108","https://openalex.org/W1522301498","https://openalex.org/W1597727245","https://openalex.org/W1783315696","https://openalex.org/W1831449718","https://openalex.org/W1903029394","https://openalex.org/W1924619199","https://openalex.org/W1977194745","https://openalex.org/W1985949187","https://openalex.org/W2007640671","https://openalex.org/W2028763589","https://openalex.org/W2031489346","https://openalex.org/W2035773017","https://openalex.org/W2077604257","https://openalex.org/W2103917701","https://openalex.org/W2109815552","https://openalex.org/W2113137767","https://openalex.org/W2114867966","https://openalex.org/W2115548755","https://openalex.org/W2117539524","https://openalex.org/W2124351162","https://openalex.org/W2125188192","https://openalex.org/W2125637308","https://openalex.org/W2128254161","https://openalex.org/W2133515615","https://openalex.org/W2136831404","https://openalex.org/W2144794286","https://openalex.org/W2147318913","https://openalex.org/W2150721269","https://openalex.org/W2154571593","https://openalex.org/W2155893237","https://openalex.org/W2156936307","https://openalex.org/W2166802795","https://openalex.org/W2169040970","https://openalex.org/W2169551590","https://openalex.org/W2170240176","https://openalex.org/W2193413348","https://openalex.org/W2194775991","https://openalex.org/W2221898772","https://openalex.org/W2256362396","https://openalex.org/W2295130376","https://openalex.org/W2306289963","https://openalex.org/W2331128040","https://openalex.org/W2337429362","https://openalex.org/W2467473805","https://openalex.org/W2518810941","https://openalex.org/W2519481857","https://openalex.org/W2520247582","https://openalex.org/W2555510177","https://openalex.org/W2604469346","https://openalex.org/W2604909019","https://openalex.org/W2609883120","https://openalex.org/W2613041730","https://openalex.org/W2630837129","https://openalex.org/W2771305881","https://openalex.org/W2779176852","https://openalex.org/W2919115771","https://openalex.org/W2948606054","https://openalex.org/W2950094539","https://openalex.org/W2962754725","https://openalex.org/W2962914239","https://openalex.org/W2963012544","https://openalex.org/W2963198662","https://openalex.org/W2963452532","https://openalex.org/W2963687373","https://openalex.org/W2963767233","https://openalex.org/W2963774720","https://openalex.org/W2963826371","https://openalex.org/W2963840672","https://openalex.org/W2963891416","https://openalex.org/W2963920537","https://openalex.org/W2963928582","https://openalex.org/W2964013315","https://openalex.org/W2964121744","https://openalex.org/W2985194834","https://openalex.org/W3035302306","https://openalex.org/W3104724358","https://openalex.org/W3105901005","https://openalex.org/W3128913384","https://openalex.org/W4248635988","https://openalex.org/W4250617962","https://openalex.org/W4252179328","https://openalex.org/W4254912136","https://openalex.org/W4285719527","https://openalex.org/W4297749385","https://openalex.org/W4297801963","https://openalex.org/W4308909683","https://openalex.org/W4385490361","https://openalex.org/W6631190155","https://openalex.org/W6635726302","https://openalex.org/W6638670064","https://openalex.org/W6640174519","https://openalex.org/W6647720530","https://openalex.org/W6675705777","https://openalex.org/W6684667240","https://openalex.org/W6685053522","https://openalex.org/W6687566353","https://openalex.org/W6696085341","https://openalex.org/W6697028695","https://openalex.org/W6736321337","https://openalex.org/W6739696289","https://openalex.org/W6745858788","https://openalex.org/W6752591435","https://openalex.org/W6775113144"],"related_works":["https://openalex.org/W2053349965","https://openalex.org/W1518796764","https://openalex.org/W347294048","https://openalex.org/W2118841422","https://openalex.org/W2226908759","https://openalex.org/W2061881449","https://openalex.org/W1483822002","https://openalex.org/W1899667806","https://openalex.org/W2351116219","https://openalex.org/W2110536527"],"abstract_inverted_index":{"The":[0],"current":[1],"gold":[2],"standard":[3],"in":[4,30],"solving":[5],"image":[6,36,40,42,57,208,212],"processing":[7],"and":[8,48,210,220,229],"computer":[9],"vision":[10],"tasks":[11],"is":[12,34,61,72,152],"using":[13,111],"supervised":[14,81,236],"learning":[15],"of":[16,24,55,76,95,108,121,139,217],"deep":[17],"neural":[18],"networks":[19],"(DNNs),":[20],"requiring":[21],"large-scale":[22],"datasets":[23],"input-output":[25],"pairs.":[26],"In":[27],"many":[28],"scenarios":[29],"which":[31],"the":[32,53,93,103,140,164,177,189,224],"output":[33,141,165],"an":[35,73,127],"-":[37,52],"e.g.,":[38],"medical":[39],"analysis,":[41],"denoising,":[43],"deblurring,":[44],"super-resolution,":[45],"dehazing,":[46,213],"segmentation":[47],"optical":[49],"flow":[50],"estimation":[51],"collection":[54],"labelled":[56,193],"pairs":[58],"for":[59,154],"training":[60,99],"either":[62],"time-consuming":[63],"or":[64,195],"limited":[65],"to":[66,145,176,183,234],"simple":[67],"degradation":[68],"models.":[69],"Indeed,":[70],"there":[71],"increasing":[74],"body":[75],"work":[77,90],"targeted":[78],"at":[79],"weakly":[80],"training,":[82],"accompanied":[83],"with":[84,106,126,166,232],"different":[85,204],"unsupervised":[86,132],"loss":[87,105,178],"functions.":[88],"This":[89],"dives":[91],"into":[92],"regime":[94],"Deep-Energy,":[96],"a":[97,119,122,167],"task-driven":[98],"approach":[100,201],"that":[101],"substitutes":[102],"generic":[104],"minimization":[107,227],"energy":[109,114,147,226],"functions":[110],"DNNs.":[112],"Such":[113],"functions,":[115],"often":[116],"formulated":[117],"as":[118,133],"combination":[120],"data-fidelity":[123],"term":[124],"along":[125],"application-specific":[128,173],"prior,":[129],"are":[130,181],"essentially":[131],"they":[134],"do":[135],"not":[136],"assume":[137],"knowledge":[138,175],"image.":[142],"As":[143],"opposed":[144],"classic":[146],"minimization,":[148],"where":[149],"computationally-intensive":[150],"inference":[151],"performed":[153],"each":[155],"new":[156],"image,":[157],"our":[158,200],"network,":[159],"once":[160],"trained,":[161],"can":[162],"compute":[163],"single":[168,211],"forward-pass":[169],"operation.":[170],"By":[171],"incorporating":[172],"domain":[174],"function,":[179],"we":[180],"able":[182],"use":[184],"real-world":[185],"images,":[186],"thus":[187],"decreasing":[188],"dependency":[190],"on":[191,202],"pixel-wise":[192],"data":[194],"synthetic":[196],"datasets.":[197],"We":[198],"demonstrate":[199],"three":[203],"applications:":[205],"seeded":[206],"segmentation,":[207],"matting":[209],"showing":[214],"clear":[215],"benefits":[216],"both":[218],"speedup":[219],"improved":[221],"accuracy":[222],"versus":[223],"classical":[225],"approach,":[228],"competitive":[230],"performance":[231],"respect":[233],"fully":[235],"alternatives.":[237]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2019-08-29T00:00:00"}
