{"id":"https://openalex.org/W4294310844","doi":"https://doi.org/10.1109/jstars.2022.3203750","title":"Semi-supervised Deep Learning via Transformation Consistency Regularization for Remote Sensing Image Semantic Segmentation","display_name":"Semi-supervised Deep Learning via Transformation Consistency Regularization for Remote Sensing Image Semantic Segmentation","publication_year":2022,"publication_date":"2022-09-02","ids":{"openalex":"https://openalex.org/W4294310844","doi":"https://doi.org/10.1109/jstars.2022.3203750"},"language":"en","primary_location":{"id":"doi:10.1109/jstars.2022.3203750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3203750","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09875010.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09875010.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100392796","display_name":"Bin Zhang","orcid":"https://orcid.org/0000-0001-9545-2760"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bin Zhang","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108625236","display_name":"Yongjun Zhang","orcid":"https://orcid.org/0000-0001-9845-4251"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjun Zhang","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100606147","display_name":"Yansheng Li","orcid":"https://orcid.org/0000-0001-8203-1246"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yansheng Li","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110992629","display_name":"Yi Wan","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Wan","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106665185","display_name":"Haoyu Guo","orcid":"https://orcid.org/0000-0002-2939-6294"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoyu Guo","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101676159","display_name":"Zhi Zheng","orcid":"https://orcid.org/0009-0004-8746-0591"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Zheng","raw_affiliation_strings":["Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"Department of Photogrammetry, School of Remote Sensing and Information Engineering, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100435639","display_name":"Kun Yang","orcid":"https://orcid.org/0000-0002-6782-6689"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kun Yang","raw_affiliation_strings":["Basic Geographic Information Center of Guizhou Province, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"Basic Geographic Information Center of Guizhou Province, Guizhou, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5100392796"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":{"value":1250,"currency":"USD","value_usd":1250},"apc_paid":{"value":1250,"currency":"USD","value_usd":1250},"fwci":4.8468,"has_fulltext":true,"cited_by_count":44,"citation_normalized_percentile":{"value":0.95779929,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"16","issue":null,"first_page":"5782","last_page":"5796"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9947999715805054,"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":0.9939000010490417,"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":0.782381534576416},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7010971307754517},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.6969633102416992},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6147249341011047},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5857203006744385},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5766727924346924},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5422608852386475},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.505165159702301},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49823832511901855},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.45435819029808044},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.4421304762363434},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.4243684411048889},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.41404274106025696},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3226024806499481}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.782381534576416},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7010971307754517},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.6969633102416992},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6147249341011047},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5857203006744385},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5766727924346924},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5422608852386475},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.505165159702301},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49823832511901855},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.45435819029808044},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.4421304762363434},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.4243684411048889},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.41404274106025696},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3226024806499481},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstars.2022.3203750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3203750","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09875010.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:572f1e824962425bbd68d67f17f7e569","is_oa":true,"landing_page_url":"https://doaj.org/article/572f1e824962425bbd68d67f17f7e569","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 5782-5796 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/jstars.2022.3203750","is_oa":true,"landing_page_url":"https://doi.org/10.1109/jstars.2022.3203750","pdf_url":"https://ieeexplore.ieee.org/ielx7/4609443/9973430/09875010.pdf","source":{"id":"https://openalex.org/S117727964","display_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","issn_l":"1939-1404","issn":["1939-1404","2151-1535"],"is_oa":true,"is_in_doaj":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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.6899999976158142,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1356514951","display_name":null,"funder_award_id":"41971","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2708589882","display_name":null,"funder_award_id":"41971284","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3658866185","display_name":null,"funder_award_id":"42030102","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4310224551","display_name":null,"funder_award_id":"419712","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7174558747","display_name":null,"funder_award_id":"Group","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4294310844.pdf","grobid_xml":"https://content.openalex.org/works/W4294310844.grobid-xml"},"referenced_works_count":73,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1923697677","https://openalex.org/W1970144159","https://openalex.org/W2095483845","https://openalex.org/W2142012908","https://openalex.org/W2153409933","https://openalex.org/W2187089797","https://openalex.org/W2194775991","https://openalex.org/W2321533354","https://openalex.org/W2412588858","https://openalex.org/W2412782625","https://openalex.org/W2488187315","https://openalex.org/W2527276685","https://openalex.org/W2560023338","https://openalex.org/W2609825896","https://openalex.org/W2630837129","https://openalex.org/W2764034829","https://openalex.org/W2768975974","https://openalex.org/W2770429219","https://openalex.org/W2778539913","https://openalex.org/W2778764040","https://openalex.org/W2782522152","https://openalex.org/W2795547044","https://openalex.org/W2804199516","https://openalex.org/W2804860796","https://openalex.org/W2897760800","https://openalex.org/W2898947732","https://openalex.org/W2899319425","https://openalex.org/W2902746003","https://openalex.org/W2909158354","https://openalex.org/W2919115771","https://openalex.org/W2940726923","https://openalex.org/W2955058313","https://openalex.org/W2957972995","https://openalex.org/W2963995737","https://openalex.org/W2964159205","https://openalex.org/W2970574533","https://openalex.org/W2989484703","https://openalex.org/W2992308087","https://openalex.org/W2995808743","https://openalex.org/W3000978536","https://openalex.org/W3007268491","https://openalex.org/W3025926153","https://openalex.org/W3034749675","https://openalex.org/W3035680157","https://openalex.org/W3040988483","https://openalex.org/W3047233942","https://openalex.org/W3048064159","https://openalex.org/W3107695429","https://openalex.org/W3119804198","https://openalex.org/W3129983770","https://openalex.org/W3157967435","https://openalex.org/W3159993994","https://openalex.org/W3171581326","https://openalex.org/W3202294484","https://openalex.org/W3205020875","https://openalex.org/W3209458476","https://openalex.org/W4210606444","https://openalex.org/W4214945166","https://openalex.org/W6617210626","https://openalex.org/W6717772578","https://openalex.org/W6722710385","https://openalex.org/W6733814495","https://openalex.org/W6739696289","https://openalex.org/W6745136726","https://openalex.org/W6748692255","https://openalex.org/W6762913911","https://openalex.org/W6764051988","https://openalex.org/W6767327284","https://openalex.org/W6768220425","https://openalex.org/W6773005947","https://openalex.org/W6779659972"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2358755282","https://openalex.org/W2625833328","https://openalex.org/W1533177136","https://openalex.org/W4380994516","https://openalex.org/W2237505347"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3,31],"have":[4],"gotten":[5],"a":[6,35,47,99,162,170,182],"lot":[7],"of":[8,38,50,66,110,117,121,178,239,259],"press":[9],"in":[10,16,68,74,206,237],"the":[11,75,107,118,152,203,218,252,257],"last":[12],"several":[13],"years,":[14],"especially":[15,59,72],"domains":[17],"like":[18],"computer":[19],"vision":[20],"and":[21,56,124,155,189,232],"remote":[22],"sensing":[23],"(RS).":[24],"However,":[25],"achieving":[26],"superior":[27],"performance":[28],"with":[29],"deep":[30,102,163],"highly":[32],"depends":[33],"on":[34,186,195,212],"massive":[36],"number":[37,49],"accurately":[39],"labeled":[40,51,81,122,187,261],"training":[41],"samples.":[42,127],"In":[43,94],"real-world":[44],"applications,":[45],"gathering":[46],"large":[48],"samples":[52,82,188,226,262],"is":[53,71],"time":[54],"consuming":[55],"labor":[57],"intensive,":[58],"for":[60,106,263],"pixel-level":[61],"data":[62,90],"annotation.":[63],"This":[64],"dearth":[65],"labels":[67],"land-cover":[69,267],"classification":[70],"pressing":[73],"RS":[76,112,214,265],"domain":[77],"because":[78],"high-precision":[79],"high-quality":[80],"are":[83,91],"extremely":[84],"difficult":[85],"to":[86,114,134,150,201,227,254],"acquire,":[87],"but":[88],"unlabeled":[89,126,196,225],"readily":[92],"available.":[93],"this":[95],"study,":[96],"we":[97,160],"offer":[98],"new":[100],"semisupervised":[101,164,235,247],"semantic":[103,108,165,248],"labeling":[104,166,249],"framework":[105],"segmentation":[109],"high-resolution":[111,264],"images":[113],"take":[115],"advantage":[116],"limited":[119,260],"amount":[120],"examples":[123],"numerous":[125],"Our":[128,209,241],"model":[129],"uses":[130],"transformation":[131,172],"consistency":[132,153,173],"regularization":[133,192],"encourage":[135],"consistent":[136],"network":[137,204],"predictions":[138,231],"under":[139],"different":[140,148],"random":[141],"transformations":[142],"or":[143],"perturbations.":[144],"We":[145],"try":[146],"three":[147],"transforms":[149],"compute":[151],"loss":[154],"analyze":[156],"their":[157],"performance.":[158,240],"Then,":[159],"present":[161],"technique":[167],"by":[168],"using":[169],"hybrid":[171],"regularization.":[174],"A":[175],"weighted":[176],"sum":[177],"losses,":[179],"which":[180],"contains":[181],"supervised":[183],"term":[184,193],"computed":[185,194],"an":[190],"unsupervised":[191],"data,":[197],"may":[198],"be":[199],"used":[200],"update":[202],"parameters":[205],"our":[207,246],"technique.":[208],"comprehensive":[210],"experiments":[211,242],"two":[213],"datasets":[215],"confirmed":[216],"that":[217,245],"suggested":[219],"approach":[220],"utilized":[221],"latent":[222],"information":[223],"from":[224],"obtain":[228],"more":[229],"precise":[230],"outperformed":[233],"existing":[234],"algorithms":[236],"terms":[238],"further":[243],"demonstrated":[244],"strategy":[250],"has":[251],"potential":[253],"partially":[255],"tackle":[256],"problem":[258],"image":[266],"segmentation.":[268]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":17},{"year":2023,"cited_by_count":10}],"updated_date":"2026-03-18T14:38:29.013473","created_date":"2025-10-10T00:00:00"}
