{"id":"https://openalex.org/W3090393225","doi":"https://doi.org/10.1109/icip40778.2020.9190850","title":"Semi-Supervised Multi-Spectral Land Cover Classification With Multi-Attention and Adaptive Kernel","display_name":"Semi-Supervised Multi-Spectral Land Cover Classification With Multi-Attention and Adaptive Kernel","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3090393225","doi":"https://doi.org/10.1109/icip40778.2020.9190850","mag":"3090393225"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9190850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9190850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100459344","display_name":"Kexin Zhang","orcid":"https://orcid.org/0000-0003-1968-8004"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kexin Zhang","raw_affiliation_strings":["Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101850450","display_name":"Hua Yang","orcid":"https://orcid.org/0009-0000-1050-6177"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hua Yang","raw_affiliation_strings":["Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Communication and Network Engineering, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1881","last_page":"1885"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9998000264167786,"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":0.9998000264167786,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.98089998960495,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7221664786338806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7125358581542969},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.7096853256225586},{"id":"https://openalex.org/keywords/land-cover","display_name":"Land cover","score":0.6134079694747925},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5425248146057129},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5412781238555908},{"id":"https://openalex.org/keywords/multispectral-pattern-recognition","display_name":"Multispectral pattern recognition","score":0.5225943326950073},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5015068054199219},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.49941301345825195},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.47650662064552307},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4760144352912903},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.4399682283401489},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4297633171081543},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.42452430725097656},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3595650792121887},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34414762258529663},{"id":"https://openalex.org/keywords/land-use","display_name":"Land use","score":0.17788642644882202},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1436253786087036},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13515043258666992},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1268264651298523}],"concepts":[{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7221664786338806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7125358581542969},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.7096853256225586},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.6134079694747925},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5425248146057129},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5412781238555908},{"id":"https://openalex.org/C104541649","wikidata":"https://www.wikidata.org/wiki/Q6935090","display_name":"Multispectral pattern recognition","level":3,"score":0.5225943326950073},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5015068054199219},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.49941301345825195},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.47650662064552307},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4760144352912903},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.4399682283401489},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4297633171081543},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.42452430725097656},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3595650792121887},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34414762258529663},{"id":"https://openalex.org/C4792198","wikidata":"https://www.wikidata.org/wiki/Q1165944","display_name":"Land use","level":2,"score":0.17788642644882202},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1436253786087036},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13515043258666992},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1268264651298523},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C147176958","wikidata":"https://www.wikidata.org/wiki/Q77590","display_name":"Civil engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9190850","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9190850","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W2173520492","https://openalex.org/W2183341477","https://openalex.org/W2461261958","https://openalex.org/W2513378248","https://openalex.org/W2747638294","https://openalex.org/W2757208835","https://openalex.org/W2762941833","https://openalex.org/W2783165089","https://openalex.org/W2792261129","https://openalex.org/W2792416626","https://openalex.org/W2902746003","https://openalex.org/W2913012226","https://openalex.org/W2922509574","https://openalex.org/W2923040790","https://openalex.org/W2948157022","https://openalex.org/W2963373786","https://openalex.org/W2963420686","https://openalex.org/W2963684088","https://openalex.org/W2964121744","https://openalex.org/W2964194231","https://openalex.org/W4237192424","https://openalex.org/W4288622677","https://openalex.org/W6631190155","https://openalex.org/W6685352114","https://openalex.org/W6718379498","https://openalex.org/W6719167098","https://openalex.org/W6743731764","https://openalex.org/W6759000249"],"related_works":["https://openalex.org/W2128126485","https://openalex.org/W4382563209","https://openalex.org/W2124952510","https://openalex.org/W2777937183","https://openalex.org/W2108633818","https://openalex.org/W1752760603","https://openalex.org/W1995889410","https://openalex.org/W4389779246","https://openalex.org/W1517037119","https://openalex.org/W2125510194"],"abstract_inverted_index":{"Land":[0],"cover":[1,45],"classification":[2,34],"is":[3,76,111],"one":[4,67],"vital":[5],"and":[6,20,38,48,62,86],"challenging":[7],"task":[8],"in":[9,60,83],"remote":[10],"sensing":[11],"(RS)":[12],"field.":[13],"Tackling":[14],"the":[15,71,96,106],"limited":[16],"labeled":[17,109],"training":[18],"data":[19,110],"for":[21],"exploiting":[22],"abundant":[23],"information":[24],"of":[25,108],"multispectral":[26,33],"bands,":[27],"we":[28,65],"proposed":[29,97],"a":[30],"novel":[31],"semi-supervised":[32],"network":[35],"with":[36],"multi-attention":[37,68],"adaptive":[39,72],"kernel.":[40],"We":[41],"select":[42],"10":[43],"land":[44],"related":[46],"bands":[47],"combine":[49],"them":[50],"into":[51],"different":[52],"spectral":[53,61],"groups.":[54],"To":[55],"further":[56],"extract":[57],"discriminating":[58],"feature":[59],"spatial":[63],"dimension,":[64],"design":[66],"block.":[69],"Furthermore,":[70],"receptive":[73],"field":[74],"mechanism":[75],"introduced":[77],"to":[78],"dynamically":[79],"adjust":[80],"kernel":[81],"size":[82],"convolution":[84],"layer":[85],"aggregate":[87],"multi-scale":[88],"information.":[89],"Experiments":[90],"on":[91],"EuroSAT":[92],"dataset":[93],"demonstrate":[94],"that":[95],"method":[98],"can":[99],"outperform":[100],"greatly":[101],"state-of-the-art":[102],"methods,":[103],"especially":[104],"when":[105],"number":[107],"relatively":[112],"small.":[113]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2021,"cited_by_count":4}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
