{"id":"https://openalex.org/W7118250295","doi":"https://doi.org/10.1109/indin64977.2025.11279524","title":"Lightweight Multi-Scale Crop Classification Network with Dense Dilated Convolutions","display_name":"Lightweight Multi-Scale Crop Classification Network with Dense Dilated Convolutions","publication_year":2025,"publication_date":"2025-07-12","ids":{"openalex":"https://openalex.org/W7118250295","doi":"https://doi.org/10.1109/indin64977.2025.11279524"},"language":null,"primary_location":{"id":"doi:10.1109/indin64977.2025.11279524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","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/A5083767275","display_name":"Tianyu Ren","orcid":null},"institutions":[{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"TianYu Ren","raw_affiliation_strings":["Yangzhou University,School of Information Engineering,Yangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yangzhou University,School of Information Engineering,Yangzhou,China","institution_ids":["https://openalex.org/I78978612"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112428693","display_name":"Qingqing Hong","orcid":null},"institutions":[{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"QingQing Hong","raw_affiliation_strings":["Yangzhou University,School of Information Engineering,Yangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yangzhou University,School of Information Engineering,Yangzhou,China","institution_ids":["https://openalex.org/I78978612"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122046939","display_name":"Wei Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Liu","raw_affiliation_strings":["Yangzhou University,School of Information Engineering,Yangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yangzhou University,School of Information Engineering,Yangzhou,China","institution_ids":["https://openalex.org/I78978612"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103192061","display_name":"Yue Zhu","orcid":"https://orcid.org/0009-0009-1401-364X"},"institutions":[{"id":"https://openalex.org/I78978612","display_name":"Yangzhou University","ror":"https://ror.org/03tqb8s11","country_code":"CN","type":"education","lineage":["https://openalex.org/I78978612"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Zhu","raw_affiliation_strings":["Yangzhou University,School of Information Engineering,Yangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yangzhou University,School of Information Engineering,Yangzhou,China","institution_ids":["https://openalex.org/I78978612"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I78978612"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.34769999980926514,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.34769999980926514,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.11869999766349792,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.11089999973773956,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6266000270843506},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5964000225067139},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5799999833106995},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.43220001459121704},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.41769999265670776},{"id":"https://openalex.org/keywords/cover","display_name":"Cover (algebra)","score":0.3747999966144562},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.35190001130104065},{"id":"https://openalex.org/keywords/row","display_name":"Row","score":0.31859999895095825}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.718500018119812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6266000270843506},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5964000225067139},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5799999833106995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5587999820709229},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.43220001459121704},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.41769999265670776},{"id":"https://openalex.org/C2780428219","wikidata":"https://www.wikidata.org/wiki/Q16952335","display_name":"Cover (algebra)","level":2,"score":0.3747999966144562},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.31790000200271606},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.31690001487731934},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.31200000643730164},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3109999895095825},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.3075000047683716},{"id":"https://openalex.org/C2780648208","wikidata":"https://www.wikidata.org/wiki/Q3001793","display_name":"Land cover","level":3,"score":0.30070000886917114},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C2988224531","wikidata":"https://www.wikidata.org/wiki/Q20830730","display_name":"Network structure","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/indin64977.2025.11279524","is_oa":false,"landing_page_url":"https://doi.org/10.1109/indin64977.2025.11279524","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE 23rd International Conference on Industrial Informatics (INDIN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1990653740","https://openalex.org/W2056435747","https://openalex.org/W2132424470","https://openalex.org/W2302255633","https://openalex.org/W2523311857","https://openalex.org/W2604086375","https://openalex.org/W2743142445","https://openalex.org/W2884585870","https://openalex.org/W2910478295","https://openalex.org/W2920930972","https://openalex.org/W2948329096","https://openalex.org/W2963420686","https://openalex.org/W2982083293","https://openalex.org/W3177052299","https://openalex.org/W4226334005","https://openalex.org/W4285395418","https://openalex.org/W4312349930","https://openalex.org/W4312777001","https://openalex.org/W4312849152","https://openalex.org/W4312881242","https://openalex.org/W4365136950"],"related_works":[],"abstract_inverted_index":{"In":[0],"traditional":[1],"land":[2],"cover":[3],"classification":[4],"tasks":[5],"based":[6],"on":[7,13],"CNNs,":[8],"spatial":[9],"feature":[10,91],"extraction":[11],"relies":[12],"fixed":[14],"receptive":[15],"fields.":[16],"However,":[17],"this":[18,32],"approach":[19],"has":[20],"a":[21,36,73],"significant":[22],"drawback:":[23],"the":[24,87],"lack":[25],"of":[26,99],"multi-scale":[27,37,53,67],"information":[28],"modeling.":[29],"To":[30],"address":[31],"issue,":[33],"we":[34,71],"propose":[35],"convolutional":[38,101],"network":[39],"with":[40],"dense":[41,57],"short":[42],"connections.":[43],"Our":[44],"innovative":[45],"design":[46],"employs":[47],"depthwise":[48],"dilated":[49],"convolutions":[50],"to":[51,59,76],"extract":[52],"features":[54],"and":[55,83,105,120],"utilizes":[56],"connections":[58],"interlink":[60],"these":[61],"features,":[62],"constructing":[63],"progressively":[64],"advanced":[65],"intra-layer":[66],"hierarchical":[68],"structures.":[69],"Additionally,":[70],"introduce":[72],"Coordinate":[74],"Attention":[75],"establish":[77],"dual-dimensional":[78],"weight":[79],"mappings":[80],"across":[81,96],"scales":[82],"channels,":[84],"thereby":[85],"enhancing":[86],"relationships":[88],"between":[89],"different":[90],"maps.":[92],"Through":[93],"comparative":[94],"experiments":[95],"three":[97],"types":[98],"models\u2014classical":[100],"networks,":[102],"lightweight":[103],"models,":[104],"Transformer-based":[106],"architectures,":[107],"encompassing":[108],"nine":[109],"experimental":[110],"setups\u2014our":[111],"model":[112],"demonstrates":[113],"superior":[114],"accuracy":[115],"while":[116],"maintaining":[117],"lower":[118],"computational":[119],"storage":[121],"costs.":[122]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-08T00:00:00"}
