{"id":"https://openalex.org/W2991453722","doi":"https://doi.org/10.1109/lsp.2019.2956367","title":"Batching Soft IoU for Training Semantic Segmentation Networks","display_name":"Batching Soft IoU for Training Semantic Segmentation Networks","publication_year":2019,"publication_date":"2019-11-28","ids":{"openalex":"https://openalex.org/W2991453722","doi":"https://doi.org/10.1109/lsp.2019.2956367","mag":"2991453722"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2019.2956367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2956367","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_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 Signal Processing Letters","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/A5103158590","display_name":"Yifeng Huang","orcid":"https://orcid.org/0000-0001-8548-630X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yifeng Huang","raw_affiliation_strings":["Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101785677","display_name":"Zhirong Tang","orcid":"https://orcid.org/0000-0002-8146-8208"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhirong Tang","raw_affiliation_strings":["Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101775102","display_name":"Dan Chen","orcid":"https://orcid.org/0000-0003-1635-229X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Chen","raw_affiliation_strings":["Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089923142","display_name":"Kaixiong Su","orcid":"https://orcid.org/0000-0001-8431-9323"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kaixiong Su","raw_affiliation_strings":["Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101617720","display_name":"Chengbin Chen","orcid":"https://orcid.org/0000-0001-7210-1407"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengbin Chen","raw_affiliation_strings":["Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"Institute of Physics and Information Engineering, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5103158590"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":1.5328,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.86819353,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"27","issue":null,"first_page":"66","last_page":"70"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7629458904266357},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6559770107269287},{"id":"https://openalex.org/keywords/randomness","display_name":"Randomness","score":0.5106766819953918},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.49147045612335205},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4853912591934204},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.4507449269294739},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4438045024871826},{"id":"https://openalex.org/keywords/cross-entropy","display_name":"Cross entropy","score":0.43273937702178955},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42264288663864136},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3421631455421448},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.25770488381385803},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14732429385185242},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09888350963592529}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7629458904266357},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6559770107269287},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.5106766819953918},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.49147045612335205},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4853912591934204},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.4507449269294739},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4438045024871826},{"id":"https://openalex.org/C167981619","wikidata":"https://www.wikidata.org/wiki/Q1685498","display_name":"Cross entropy","level":3,"score":0.43273937702178955},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42264288663864136},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3421631455421448},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.25770488381385803},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14732429385185242},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09888350963592529},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2019.2956367","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2019.2956367","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_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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W172260869","https://openalex.org/W1584308190","https://openalex.org/W1836465849","https://openalex.org/W1903029394","https://openalex.org/W2480078828","https://openalex.org/W2557283755","https://openalex.org/W2560311620","https://openalex.org/W2607786368","https://openalex.org/W2607943185","https://openalex.org/W2609077090","https://openalex.org/W2622263826","https://openalex.org/W2734349601","https://openalex.org/W2765982206","https://openalex.org/W2784226479","https://openalex.org/W2795587607","https://openalex.org/W2799042347","https://openalex.org/W2893459692","https://openalex.org/W2945070549","https://openalex.org/W2949117887","https://openalex.org/W2950187406","https://openalex.org/W2962676885","https://openalex.org/W2962766617","https://openalex.org/W2962782553","https://openalex.org/W2962914239","https://openalex.org/W2963351448","https://openalex.org/W2963433607","https://openalex.org/W2963691377","https://openalex.org/W2963833733","https://openalex.org/W4297736277","https://openalex.org/W6638667902","https://openalex.org/W6736479369","https://openalex.org/W6739622702","https://openalex.org/W6740984670","https://openalex.org/W6750964650","https://openalex.org/W6754956192"],"related_works":["https://openalex.org/W3034924094","https://openalex.org/W3094954546","https://openalex.org/W1488708774","https://openalex.org/W2981906196","https://openalex.org/W4391100477","https://openalex.org/W4286681602","https://openalex.org/W3209312100","https://openalex.org/W3186841937","https://openalex.org/W4287010045","https://openalex.org/W2944415726"],"abstract_inverted_index":{"The":[0,61,75],"majority":[1],"of":[2,82,95,109,130,138,161],"semantic":[3],"segmentation":[4,73,159],"networks":[5],"generally":[6],"employ":[7],"cross-entropy":[8],"as":[9,16,25],"a":[10,26,44,71],"loss":[11,27,36,68,140,171],"function":[12,28,37,69,172],"and":[13,38,164],"intersection-over-union":[14],"(IoU)":[15],"the":[17,31,35,39,66,83,93,99,107,110,121,127,131,136,144,148,158,162],"evaluation":[18,40],"metric":[19],"for":[20],"network":[21,163],"performance.":[22],"Employing":[23],"IoU":[24,46,67,139,170],"can":[29],"solve":[30],"mismatch":[32],"issue":[33],"between":[34],"metric.":[41],"We":[42],"propose":[43],"Soft":[45,53],"training":[47,84,118],"strategy":[48],"based":[49],"on":[50,147],"mini-batch":[51,112,122],"(mini-batch":[52],"IoU).":[54],"Our":[55,104],"work":[56],"has":[57],"two":[58],"primary":[59],"contributions:":[60],"first":[62],"is":[63,77],"to":[64,70,78,98],"extend":[65],"multi-class":[72],"network.":[74],"second":[76],"collect":[79],"various":[80],"categories":[81,96],"samples":[85,119],"in":[86,120],"every":[87],"mini-batch,":[88],"which":[89],"will":[90],"ensure":[91],"that":[92,153],"number":[94],"equals":[97],"batch":[100],"size":[101],"at":[102],"least.":[103],"method":[105,155],"breaks":[106],"randomness":[108],"original":[111],"gradient":[113],"descent":[114],"(GD)":[115],"strategy,":[116],"advancing":[117],"much":[123],"more":[124],"consistent":[125],"with":[126],"distribution":[128],"characteristics":[129],"overall":[132],"data.":[133],"It":[134],"solves":[135],"instability":[137],"function.":[141],"In":[142],"addition,":[143],"experimental":[145],"results":[146],"PASCAL":[149],"VOC2012":[150],"dataset":[151],"reveal":[152],"our":[154],"effectively":[156],"improves":[157],"accuracy":[160],"attains":[165],"significant":[166],"improvements":[167],"beyond":[168],"state-of-the-art":[169],"methods.":[173]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":20},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":3}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}