{"id":"https://openalex.org/W4292449115","doi":"https://doi.org/10.3233/jifs-213506","title":"Hybrid connected attentional lightweight network for gangue intelligent segmentation in top-coal caving face","display_name":"Hybrid connected attentional lightweight network for gangue intelligent segmentation in top-coal caving face","publication_year":2022,"publication_date":"2022-08-05","ids":{"openalex":"https://openalex.org/W4292449115","doi":"https://doi.org/10.3233/jifs-213506"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-213506","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-213506","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","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/A5101119565","display_name":"Chengcai Fu","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengcai Fu","raw_affiliation_strings":["School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069770026","display_name":"Fengli Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengli Lu","raw_affiliation_strings":["School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647662","display_name":"Fan Wu","orcid":"https://orcid.org/0000-0003-0156-568X"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fan Wu","raw_affiliation_strings":["School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100633438","display_name":"Guoying Zhang","orcid":"https://orcid.org/0000-0002-3577-3316"},"institutions":[{"id":"https://openalex.org/I25757504","display_name":"China University of Mining and Technology","ror":"https://ror.org/01xt2dr21","country_code":"CN","type":"education","lineage":["https://openalex.org/I25757504"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guoying Zhang","raw_affiliation_strings":["School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing, China","institution_ids":["https://openalex.org/I25757504"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100633438"],"corresponding_institution_ids":["https://openalex.org/I25757504"],"apc_list":null,"apc_paid":null,"fwci":0.1989,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44155032,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"44","issue":"3","first_page":"5033","last_page":"5044"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12282","display_name":"Mineral Processing and Grinding","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T12282","display_name":"Mineral Processing and Grinding","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/T10161","display_name":"Rock Mechanics and Modeling","score":0.9922999739646912,"subfield":{"id":"https://openalex.org/subfields/2211","display_name":"Mechanics of Materials"},"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/T11073","display_name":"Metal Extraction and Bioleaching","score":0.9822999835014343,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/computer-science","display_name":"Computer science","score":0.8050824999809265},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6310538053512573},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6249133944511414},{"id":"https://openalex.org/keywords/gangue","display_name":"Gangue","score":0.5791763663291931},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.507614254951477},{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.4909978210926056},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.47527092695236206},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.448606014251709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43088269233703613},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.42926931381225586},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42461538314819336},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41987675428390503},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41901031136512756},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.20135584473609924},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1841573417186737}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8050824999809265},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6310538053512573},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6249133944511414},{"id":"https://openalex.org/C7028197","wikidata":"https://www.wikidata.org/wiki/Q1061670","display_name":"Gangue","level":2,"score":0.5791763663291931},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.507614254951477},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.4909978210926056},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.47527092695236206},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.448606014251709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43088269233703613},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.42926931381225586},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42461538314819336},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41987675428390503},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41901031136512756},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.20135584473609924},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1841573417186737},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-213506","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-213506","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent &amp; Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2016750443","https://openalex.org/W2557144775","https://openalex.org/W2762439315","https://openalex.org/W2781619231","https://openalex.org/W2791347599","https://openalex.org/W2919115771","https://openalex.org/W2943984451","https://openalex.org/W2972883427","https://openalex.org/W2979544394","https://openalex.org/W3006173852","https://openalex.org/W3011924788","https://openalex.org/W3016474591","https://openalex.org/W3022950738","https://openalex.org/W3047502985","https://openalex.org/W3088325936","https://openalex.org/W3095293036","https://openalex.org/W3119139605","https://openalex.org/W3142257492","https://openalex.org/W3163587799","https://openalex.org/W3181764854","https://openalex.org/W3190412501","https://openalex.org/W3212331021","https://openalex.org/W3213777593","https://openalex.org/W4206815672","https://openalex.org/W6776476536"],"related_works":["https://openalex.org/W3109484746","https://openalex.org/W2003353330","https://openalex.org/W2896660565","https://openalex.org/W2388863807","https://openalex.org/W2560215812","https://openalex.org/W3132983279","https://openalex.org/W2495356367","https://openalex.org/W2051113792","https://openalex.org/W4287548622","https://openalex.org/W3173347409"],"abstract_inverted_index":{"The":[0,195],"estimation":[1],"of":[2,22,41,46,116,131,139,145,168],"gangue":[3,23,70,185],"content":[4],"is":[5,24,32,67,125,156,177],"the":[6,19,39,44,74,77,111,117,128,137,143,166,174,180,184,200],"main":[7],"basis":[8],"for":[9,69],"intelligent":[10,71],"top":[11],"coal":[12],"caving":[13,79],"mining":[14],"by":[15,191],"computer":[16,27],"vision,":[17],"and":[18,43,64,95,109,113,133,162,170,183,211],"automatic":[20],"segmentation":[21,72,187],"crucial":[25],"to":[26,38,105,135,158],"vision":[28],"analysis.":[29],"However,":[30],"it":[31],"still":[33],"a":[34,52,84,101,120],"great":[35],"challenge":[36],"due":[37],"degradation":[40],"images":[42],"limitation":[45],"computing":[47],"resources.":[48],"In":[49],"this":[50],"paper,":[51],"hybrid":[53],"connected":[54],"attentional":[55],"lightweight":[56],"network":[57,176],"(HALNet)":[58],"with":[59,153,209],"high":[60,65],"speed,":[61],"few":[62],"parameters":[63,207],"accuracy":[66],"proposed":[68,175,201],"on":[73,216],"conveyor":[75],"in":[76,142],"top-coal":[78],"face.":[80],"Firstly,":[81],"we":[82],"propose":[83],"deep":[85,92],"separable":[86,93],"dilation":[87,96],"convolution":[88,94],"block":[89,151],"(DSDC)":[90],"combining":[91],"convolution,":[97],"which":[98],"can":[99],"provide":[100],"larger":[102],"receptive":[103],"field":[104],"learn":[106],"more":[107,160],"information":[108,141],"reduce":[110],"size":[112],"computational":[114],"cost":[115],"model.":[118],"Secondly,":[119],"bridging":[121],"residual":[122],"learning":[123],"framework":[124],"designed":[126],"as":[127],"basic":[129],"unit":[130],"encoder":[132],"decoder":[134],"minimize":[136],"loss":[138],"semantic":[140],"process":[144],"feature":[146],"extraction.":[147],"An":[148],"attention":[149],"fusion":[150,167],"(AFB)":[152],"skip":[154],"pathway":[155],"introduced":[157],"capture":[159],"representative":[161],"distinctive":[163],"features":[164],"through":[165,179],"high-level":[169],"low-level":[171],"features.":[172],"Finally,":[173],"trained":[178],"expanded":[181],"dataset,":[182],"image":[186],"results":[188,197],"are":[189],"obtained":[190],"pixel-by-pixel":[192],"classification":[193],"method.":[194],"experimental":[196],"show":[198],"that":[199],"HALNet":[202],"reduces":[203],"about":[204],"57":[205],"percentage":[206],"compared":[208],"U-Net,":[210],"achieves":[212],"state-of-the":[213],"art":[214],"performance":[215],"dataset.":[217]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
