{"id":"https://openalex.org/W4400579926","doi":"https://doi.org/10.1109/tgrs.2024.3409903","title":"Point-Based Weakly Supervised Deep Learning for Semantic Segmentation of Remote Sensing Images","display_name":"Point-Based Weakly Supervised Deep Learning for Semantic Segmentation of Remote Sensing Images","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4400579926","doi":"https://doi.org/10.1109/tgrs.2024.3409903"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3409903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3409903","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","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/A5101921524","display_name":"Yuanhao Zhao","orcid":"https://orcid.org/0009-0008-9477-6163"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yuanhao Zhao","raw_affiliation_strings":["College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053518414","display_name":"Genyun Sun","orcid":"https://orcid.org/0000-0002-2641-2615"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Genyun Sun","raw_affiliation_strings":["College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064852606","display_name":"Ziyan Ling","orcid":"https://orcid.org/0009-0007-5652-8962"},"institutions":[{"id":"https://openalex.org/I44468530","display_name":"Qingdao University of Technology","ror":"https://ror.org/01qzc0f54","country_code":"CN","type":"education","lineage":["https://openalex.org/I44468530"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyan Ling","raw_affiliation_strings":["School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Control Engineering, Qingdao University of Technology, Qingdao, China","institution_ids":["https://openalex.org/I44468530"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074984354","display_name":"Aizhu Zhang","orcid":"https://orcid.org/0000-0003-2226-8908"},"institutions":[{"id":"https://openalex.org/I4210162190","display_name":"China University of Petroleum, East China","ror":"https://ror.org/05gbn2817","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162190"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aizhu Zhang","raw_affiliation_strings":["College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China"],"affiliations":[{"raw_affiliation_string":"College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China","institution_ids":["https://openalex.org/I4210162190"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024631382","display_name":"Xiuping Jia","orcid":"https://orcid.org/0000-0001-9916-6382"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Xiuping Jia","raw_affiliation_strings":["School of Engineering and Information Technology, University of New South Wales at Canberra, Canberra, ACT, Australia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Information Technology, University of New South Wales at Canberra, Canberra, ACT, Australia","institution_ids":["https://openalex.org/I188329596","https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101921524"],"corresponding_institution_ids":["https://openalex.org/I4210162190"],"apc_list":null,"apc_paid":null,"fwci":3.4648,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.92920443,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9990000128746033,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9972000122070312,"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":0.6891070604324341},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6684272289276123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6525524258613586},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5669021606445312},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5495766401290894},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.47294995188713074},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46407392621040344},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42371276021003723},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.34697920083999634},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.256197988986969},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08773267269134521}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6891070604324341},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6684272289276123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6525524258613586},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5669021606445312},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5495766401290894},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.47294995188713074},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46407392621040344},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42371276021003723},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.34697920083999634},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.256197988986969},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08773267269134521},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3409903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3409903","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4578672941","display_name":null,"funder_award_id":"42271347","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6412240567","display_name":null,"funder_award_id":"42101369","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8155235863","display_name":null,"funder_award_id":"42371350","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W611457968","https://openalex.org/W1495267108","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1937812750","https://openalex.org/W1945608308","https://openalex.org/W2034906331","https://openalex.org/W2068278717","https://openalex.org/W2091362016","https://openalex.org/W2143755656","https://openalex.org/W2194775991","https://openalex.org/W2291422229","https://openalex.org/W2295107390","https://openalex.org/W2306289963","https://openalex.org/W2337429362","https://openalex.org/W2520746254","https://openalex.org/W2560023338","https://openalex.org/W2618530766","https://openalex.org/W2735039185","https://openalex.org/W2782645198","https://openalex.org/W2787091153","https://openalex.org/W2799124825","https://openalex.org/W2811481004","https://openalex.org/W2894435778","https://openalex.org/W2897052332","https://openalex.org/W2903036816","https://openalex.org/W2939571759","https://openalex.org/W2940262938","https://openalex.org/W2956648669","https://openalex.org/W2963881378","https://openalex.org/W2982093251","https://openalex.org/W2982206001","https://openalex.org/W2984711682","https://openalex.org/W3003728293","https://openalex.org/W3024039333","https://openalex.org/W3034930876","https://openalex.org/W3048631361","https://openalex.org/W3094623930","https://openalex.org/W3102692100","https://openalex.org/W3104035745","https://openalex.org/W3104205547","https://openalex.org/W3105636206","https://openalex.org/W3115967667","https://openalex.org/W3121898985","https://openalex.org/W3134927667","https://openalex.org/W3164897814","https://openalex.org/W3208004344","https://openalex.org/W3214333957","https://openalex.org/W4200300905","https://openalex.org/W4221144214","https://openalex.org/W4224988756","https://openalex.org/W4225278929","https://openalex.org/W4280491288","https://openalex.org/W4310593159","https://openalex.org/W4312647976","https://openalex.org/W4323363995","https://openalex.org/W4362714336","https://openalex.org/W4366678167","https://openalex.org/W4377079779","https://openalex.org/W4388157208","https://openalex.org/W4400762160","https://openalex.org/W6761630670"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W4230611425","https://openalex.org/W2731899572","https://openalex.org/W2121524756","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W782553550","https://openalex.org/W4383066092","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Weakly":[0],"supervised":[1,81,127,186,255],"semantic":[2,26,91,135,159,198,256],"segmentation":[3,65,199,227],"methods":[4,200],"can":[5,234],"effectively":[6,235],"alleviate":[7],"the":[8,76,110,125,163,181,190,195,206,213,225,237,244,251],"problem":[9],"of":[10,97,121,155,165,215,246,253],"high":[11],"cost":[12],"and":[13,40,60,63,67,103,147,157,177,201,208,212,248],"difficult":[14],"access":[15],"to":[16,72,116,179,242],"annotation":[17,52,240],"in":[18,47,184],"traditional":[19,139],"methods.":[20],"Among":[21],"these":[22],"approaches,":[23],"point":[24,51,89,133,239],"annotated":[25,90,134],"label":[27,92],"not":[28],"only":[29],"offers":[30],"a":[31,79,118],"more":[32],"affordable":[33],"option":[34],"but":[35],"also":[36],"provides":[37],"accurate":[38],"location":[39],"category":[41],"information,":[42,62],"playing":[43],"an":[44],"indispensable":[45],"role":[46],"current":[48],"research.":[49],"However,":[50],"labeling":[53],"encounters":[54],"challenges":[55],"such":[56,143],"as":[57,144],"missing":[58],"global":[59],"texture":[61],"limiting":[64],"accuracy":[66,228,252],"efficiency":[68],"while":[69,161,232],"being":[70],"susceptible":[71],"noise":[73,166,247],"interference.":[74],"For":[75],"above":[77],"problems,":[78],"weakly":[80,126,185,254],"remote":[82],"sensing":[83],"image":[84,140],"classification":[85,168,192],"framework":[86],"based":[87],"on":[88,167,205,229],"is":[93,114,130,217],"proposed,":[94],"which":[95],"consists":[96],"three":[98],"components:":[99],"data":[100,111],"augmentation,":[101],"Pixel-Net,":[102],"iterative":[104],"superpixel-based":[105],"sample":[106],"expansion":[107],"(ISSE).":[108],"First,":[109],"augmentation":[112],"method":[113],"used":[115],"generate":[117],"sufficient":[119],"number":[120],"training":[122],"samples.":[123],"Subsequently,":[124],"network":[128],"Pixel-Net":[129,137,202,223],"trained":[131],"using":[132],"labels.":[136],"incorporates":[138],"processing":[141],"techniques":[142],"edge":[145,156],"detection":[146],"blurring":[148],"into":[149],"deep":[150],"learning,":[151],"enabling":[152],"effective":[153],"learning":[154],"spectral":[158],"details":[160],"reducing":[162],"impact":[164],"results.":[169],"Finally,":[170],"ISSE":[171,216,233],"leverages":[172],"contextual":[173],"information":[174,183],"from":[175],"superpixels":[176],"pseudo-labels":[178],"enrich":[180],"valuable":[182],"labels,":[187],"thereby":[188],"improving":[189],"model\u2019s":[191],"performance.":[193],"In":[194],"experiments,":[196],"existing":[197,238],"are":[203],"evaluated":[204],"Vaihingen":[207],"Zurich":[209],"Summer":[210],"datasets,":[211,231],"effectiveness":[214],"verified.":[218],"The":[219],"results":[220],"show":[221],"that":[222],"achieves":[224],"best":[226],"both":[230],"utilize":[236],"labels":[241],"mitigate":[243],"effect":[245],"thus":[249],"improve":[250],"segmentation.":[257]},"counts_by_year":[{"year":2025,"cited_by_count":15},{"year":2024,"cited_by_count":1}],"updated_date":"2026-03-01T08:55:55.761014","created_date":"2025-10-10T00:00:00"}
