{"id":"https://openalex.org/W3165688842","doi":"https://doi.org/10.1142/s0218001421540264","title":"Optimal Scale of Hierarchical Image Segmentation with Scribbles Guidance for Weakly Supervised Semantic Segmentation","display_name":"Optimal Scale of Hierarchical Image Segmentation with Scribbles Guidance for Weakly Supervised Semantic Segmentation","publication_year":2021,"publication_date":"2021-05-21","ids":{"openalex":"https://openalex.org/W3165688842","doi":"https://doi.org/10.1142/s0218001421540264","mag":"3165688842"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001421540264","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001421540264","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5083754382","display_name":"Zaid Al\u2010Huda","orcid":"https://orcid.org/0000-0002-8920-7635"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zaid Al-Huda","raw_affiliation_strings":["School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009537215","display_name":"Donghai Zhai","orcid":"https://orcid.org/0000-0001-8396-5710"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghai Zhai","raw_affiliation_strings":["School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068951317","display_name":"Yan Yang","orcid":"https://orcid.org/0000-0002-6134-6094"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Yang","raw_affiliation_strings":["School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"School of Computing and Artificial Intelligent, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081692024","display_name":"Riyadh Nazar Ali Algburi","orcid":"https://orcid.org/0000-0002-5412-2164"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Riyadh Nazar Ali Algburi","raw_affiliation_strings":["School of Mechanical Engineering, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Southwest Jiaotong University, 610031 Chengdu, Sichuan, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083754382"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":1.8448,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.8739103,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"35","issue":"10","first_page":"2154026","last_page":"2154026"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9994999766349792,"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/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9988999962806702,"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/segmentation","display_name":"Segmentation","score":0.8342980146408081},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7641085386276245},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7394437193870544},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.7049537897109985},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.666897714138031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6140344738960266},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6084811687469482},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.5715340375900269},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5551490783691406},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4961751401424408},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4798942804336548},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4633024334907532},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.42515045404434204},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34390509128570557}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.8342980146408081},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7641085386276245},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394437193870544},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.7049537897109985},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.666897714138031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6140344738960266},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6084811687469482},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.5715340375900269},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5551490783691406},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4961751401424408},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4798942804336548},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4633024334907532},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.42515045404434204},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34390509128570557},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001421540264","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001421540264","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":59,"referenced_works":["https://openalex.org/W105270443","https://openalex.org/W1484228140","https://openalex.org/W1495267108","https://openalex.org/W1567665801","https://openalex.org/W1783315696","https://openalex.org/W1927251054","https://openalex.org/W1945608308","https://openalex.org/W1974095883","https://openalex.org/W1999478155","https://openalex.org/W2031489346","https://openalex.org/W2059319345","https://openalex.org/W2110158442","https://openalex.org/W2117741877","https://openalex.org/W2118246710","https://openalex.org/W2124351162","https://openalex.org/W2127194945","https://openalex.org/W2133515615","https://openalex.org/W2143516773","https://openalex.org/W2144794286","https://openalex.org/W2168804568","https://openalex.org/W2216125271","https://openalex.org/W2221898772","https://openalex.org/W2291422229","https://openalex.org/W2306289963","https://openalex.org/W2337429362","https://openalex.org/W2516803306","https://openalex.org/W2519610629","https://openalex.org/W2520746254","https://openalex.org/W2559655401","https://openalex.org/W2574253917","https://openalex.org/W2600144439","https://openalex.org/W2616966451","https://openalex.org/W2739450375","https://openalex.org/W2768914434","https://openalex.org/W2796080450","https://openalex.org/W2798715809","https://openalex.org/W2799124825","https://openalex.org/W2887912047","https://openalex.org/W2894666165","https://openalex.org/W2907102629","https://openalex.org/W2911445777","https://openalex.org/W2913059114","https://openalex.org/W2921495886","https://openalex.org/W2922469884","https://openalex.org/W2947766030","https://openalex.org/W2953757691","https://openalex.org/W2954705770","https://openalex.org/W2961348656","https://openalex.org/W2963380820","https://openalex.org/W2963670239","https://openalex.org/W2964159923","https://openalex.org/W2964309882","https://openalex.org/W2976006990","https://openalex.org/W2989377148","https://openalex.org/W3002894133","https://openalex.org/W3016044592","https://openalex.org/W3050826508","https://openalex.org/W3082038009","https://openalex.org/W3111388684"],"related_works":["https://openalex.org/W3144569342","https://openalex.org/W2185902295","https://openalex.org/W2945274617","https://openalex.org/W2103507220","https://openalex.org/W2785294226","https://openalex.org/W2055202857","https://openalex.org/W1999008862","https://openalex.org/W2371519352","https://openalex.org/W4205800335","https://openalex.org/W2386644571"],"abstract_inverted_index":{"Deep":[0],"convolutional":[1],"neural":[2],"networks":[3],"(DCNNs)":[4],"trained":[5,122],"on":[6,157],"the":[7,19,66,71,78,84,95,101,115,118,125,132,145,164,177],"pixel-level":[8,55,127,152],"annotated":[9],"images":[10],"have":[11,29],"achieved":[12],"improvements":[13],"in":[14],"semantic":[15,172],"segmentation.":[16,98],"Due":[17],"to":[18,51,64,89,111,139,148],"high":[20],"cost":[21],"of":[22,74,169],"labeling":[23,41],"training":[24,116],"data,":[25],"their":[26],"applications":[27],"may":[28],"great":[30],"limitation.":[31],"However,":[32],"weakly":[33,170],"supervised":[34,171],"segmentation":[35,62,119,141,146,173],"approaches":[36],"can":[37,106],"significantly":[38],"reduce":[39],"human":[40],"efforts.":[42],"In":[43,77,114],"this":[44],"paper,":[45],"we":[46,69,134],"introduce":[47],"a":[48,59,91,136],"new":[49],"framework":[50,166],"generate":[52],"high-quality":[53,75],"initial":[54,126],"annotations.":[56,128,153],"By":[57,99],"using":[58,124],"hierarchical":[60],"image":[61],"algorithm":[63],"predict":[65],"boundary":[67],"map,":[68],"select":[70],"optimal":[72,96],"scale":[73,97],"hierarchies.":[76],"initialization":[79],"step,":[80],"scribble":[81],"annotations":[82],"and":[83,143,175],"saliency":[85],"map":[86],"are":[87],"combined":[88],"construct":[90],"graphic":[92],"model":[93,138],"over":[94],"solving":[100],"minimal":[102],"cut":[103],"problem,":[104],"it":[105],"spread":[107],"information":[108],"from":[109],"scribbles":[110],"unmarked":[112],"regions.":[113],"process,":[117],"network":[120,147],"is":[121,181],"by":[123],"To":[129],"iteratively":[130],"optimize":[131],"segmentation,":[133],"use":[135],"graphical":[137],"refine":[140],"masks":[142],"retrain":[144],"get":[149],"more":[150],"precise":[151],"The":[154],"experimental":[155],"results":[156],"Pascal":[158],"VOC":[159],"2012":[160],"dataset":[161],"demonstrate":[162],"that":[163],"proposed":[165],"outperforms":[167],"most":[168],"methods":[174],"achieves":[176],"state-of-the-art":[178],"performance,":[179],"which":[180],"[Formula:":[182],"see":[183],"text]":[184],"mIoU.":[185]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-01T17:29:45.350535","created_date":"2025-10-10T00:00:00"}
