{"id":"https://openalex.org/W7225831328","doi":"https://doi.org/10.1088/2631-8695/aec0fc","title":"AGDN: a lightweight interference-resistant model for photovoltaic panel surface damage detection under complex field conditions","display_name":"AGDN: a lightweight interference-resistant model for photovoltaic panel surface damage detection under complex field conditions","publication_year":2026,"publication_date":"2026-11-11","ids":{"openalex":"https://openalex.org/W7225831328","doi":"https://doi.org/10.1088/2631-8695/aec0fc"},"language":"en","primary_location":{"id":"doi:10.1088/2631-8695/aec0fc","doi":"https://doi.org/10.1088/2631-8695/aec0fc","is_oa":false,"landing_page_url":"https://doi.org/10.1088/2631-8695/aec0fc","pdf_url":null,"source":{"id":"https://openalex.org/S4210221144","display_name":"Engineering Research Express","issn_l":"2631-8695","issn":["2631-8695"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Research Express","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5161418942","display_name":"Hongxiang Li","orcid":"https://orcid.org/0009-0008-8489-6719","observed_orcids":["https://orcid.org/0009-0008-8489-6719"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxiang Li","raw_affiliation_strings":["Xinjiang University"],"raw_orcid":"https://orcid.org/0009-0008-8489-6719","affiliations":[{"raw_affiliation_string":"Xinjiang University","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161435428","display_name":"Xiangfeng Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangfeng Zhang","raw_affiliation_strings":["Xinjiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xinjiang University","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066304759","display_name":"Hong Kui Jiang","orcid":"https://orcid.org/0000-0002-6481-0278","observed_orcids":["https://orcid.org/0000-0002-6481-0278"]},"institutions":[{"id":"https://openalex.org/I96908189","display_name":"Xinjiang University","ror":"https://ror.org/059gw8r13","country_code":"CN","type":"education","lineage":["https://openalex.org/I96908189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Jiang","raw_affiliation_strings":["Xinjiang University"],"raw_orcid":"https://orcid.org/0000-0002-6481-0278","affiliations":[{"raw_affiliation_string":"Xinjiang University","institution_ids":["https://openalex.org/I96908189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101768182","display_name":"Dong Han","orcid":"https://orcid.org/0000-0003-3292-979X","observed_orcids":["https://orcid.org/0000-0003-3292-979X"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Han","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":"https://orcid.org/0000-0003-3292-979X","affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2400,"currency":"USD","value_usd":2400},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7480000257492065,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.7480000257492065,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10036","display_name":"Advanced Neural Network Applications","score":0.16249999403953552,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.07190000265836716,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.652899980545044},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5494999885559082},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.5357000231742859},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5286999940872192},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C41291067","wikidata":"https://www.wikidata.org/wiki/Q1897785","display_name":"Photovoltaic system","level":2,"score":0.5167999863624573},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.44429999589920044},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4343999922275543},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.42669999599456787},{"id":"https://openalex.org/C107551265","wikidata":"https://www.wikidata.org/wiki/Q1458245","display_name":"Displacement (psychology)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.3790000081062317},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37059998512268066},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3589000105857849},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C106195933","wikidata":"https://www.wikidata.org/wiki/Q7847935","display_name":"Truncation (statistics)","level":2,"score":0.3393999934196472},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.32839998602867126},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3203999996185303},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.3140999972820282},{"id":"https://openalex.org/C29660869","wikidata":"https://www.wikidata.org/wiki/Q5282615","display_name":"Displacement field","level":3,"score":0.3118000030517578},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3116999864578247},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.30169999599456787},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.30140000581741333},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2989000082015991},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.28279998898506165},{"id":"https://openalex.org/C4069607","wikidata":"https://www.wikidata.org/wiki/Q868732","display_name":"Aliasing","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C70000540","wikidata":"https://www.wikidata.org/wiki/Q26468","display_name":"Moir\u00e9 pattern","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.2547000050544739},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1088/2631-8695/aec0fc","doi":"https://doi.org/10.1088/2631-8695/aec0fc","is_oa":false,"landing_page_url":"https://doi.org/10.1088/2631-8695/aec0fc","pdf_url":null,"source":{"id":"https://openalex.org/S4210221144","display_name":"Engineering Research Express","issn_l":"2631-8695","issn":["2631-8695"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-d","jufo-1","norway-1","poland-20","russia-white-list-3"],"host_organization":"https://openalex.org/P4310320083","host_organization_name":"IOP Publishing","host_organization_lineage":["https://openalex.org/P4310320083","https://openalex.org/P4310311669"],"host_organization_lineage_names":["IOP Publishing","Institute of Physics"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Engineering Research Express","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"To":[1],"address":[2],"the":[3,25,48,98,114,123,138,149,210,213,235,256,271],"challenges":[4],"of":[5,118,126,191,202],"\"abnormal":[6],"feature":[7,106],"dilution\"":[8],"and":[9,62,80,93,116,140,177,189,194,199,205,218,226,240,250,263,291],"\"interference":[10],"amplification\"":[11],"in":[12,288],"photovoltaic":[13,297],"panel":[14],"surface":[15],"damage":[16,160],"detection":[17,32],"under":[18],"complex":[19],"field":[20],"conditions,":[21],"this":[22],"paper":[23],"proposes":[24],"Alignment-Gating-Discrimination":[26],"Network":[27],"(AGDN),":[28],"a":[29,52,63,109,130,166,186,232,259,264],"lightweight":[30],"object":[31],"model":[33,219,257],"built":[34],"upon":[35],"YOLO11n.":[36],"First,":[37],"an":[38,57],"enhanced":[39,244],"dynamic":[40,146],"upsampling":[41],"module,":[42],"SA-DySample,":[43],"is":[44,102,135,170],"developed":[45],"by":[46,143,223,245],"extending":[47],"DySample":[49],"framework":[50],"with":[51],"Lightweight":[53],"Channel-Aware":[54],"(LCA)":[55],"mechanism,":[56,61],"Amplitude-Aware":[58],"Stabilization":[59],"(AAS)":[60],"Flexible":[64],"Boundary":[65],"Mechanism":[66],"(FBM).":[67],"While":[68],"suppressing":[69],"background":[70],"noise":[71],"via":[72],"channel":[73],"recalibration,":[74],"SA-DySample":[75],"incorporates":[76],"magnitude-dependent":[77],"damping":[78],"constraints":[79,155],"mathematical":[81],"boundary":[82],"buffers":[83],"to":[84,112,156,172,209,296],"effectively":[85],"curb":[86],"sampling":[87],"drift,":[88],"alleviate":[89],"edge":[90],"truncation":[91],"distortion,":[92],"prevent":[94],"gradient":[95],"lock-up.":[96],"Subsequently,":[97],"SCSA":[99],"attention":[100],"module":[101],"deployed":[103,269],"after":[104],"P4":[105,139],"concatenation":[107],"as":[108],"pre-gating":[110],"unit":[111],"mitigate":[113],"co-activation":[115],"amplification":[117],"multi-source":[119],"interference":[120],"while":[121,230],"preventing":[122],"abnormal":[124],"dilution":[125],"weak":[127,159],"features.":[128],"Post-fusion,":[129],"content-adaptive":[131],"refinement":[132],"unit,":[133],"C3K2_OD,":[134],"constructed":[136],"at":[137],"P5":[141],"nodes":[142],"integrating":[144],"omni-dimensional":[145],"convolution":[147],"into":[148],"C3K2":[150],"structure,":[151],"transcending":[152],"static":[153],"parameter-sharing":[154],"precisely":[157],"differentiate":[158],"responses":[161],"from":[162],"confounding":[163],"noise.":[164],"Furthermore,":[165],"bypass-residual-free":[167],"MobileNetv1_n":[168],"backbone":[169],"adopted":[171],"minimize":[173],"memory":[174],"access":[175],"cost":[176],"computational":[178,214],"overhead.":[179],"Experimental":[180],"findings":[181],"demonstrate":[182,282],"that":[183],"AGDN":[184],"achieves":[185],"Precision,":[187,236],"Recall,":[188,234,289],"F1-Score":[190],"92.93%,":[192],"90.39%,":[193],"91.64%,":[195],"alongside":[196],"mAP50,":[197,238,292],"mAP75,":[198,239],"mAP50-95":[200,241],"metrics":[201],"94.89%,":[203],"85.40%,":[204],"80.82%,":[206],"respectively.":[207,228,254],"Compared":[208],"baseline":[211],"model,":[212],"cost,":[215],"parameter":[216],"count,":[217],"size":[220],"are":[221,242],"compressed":[222],"36.36%,":[224],"18.33%,":[225],"16.98%,":[227],"Moreover,":[229],"maintaining":[231],"comparable":[233],"F1,":[237],"significantly":[243],"4.78,":[246],"2.17,":[247],"1.05,":[248],"2.52,":[249],"3.45":[251],"percentage":[252],"points,":[253],"Additionally,":[255],"yields":[258],"35.1FPS":[260],"inference":[261],"speed":[262],"mere":[265],"28.5ms":[266],"latency":[267],"when":[268],"on":[270,278],"NVIDIA":[272],"Jetson":[273],"Orin":[274],"Nano":[275],"(FP16).":[276],"Evaluations":[277],"two":[279],"public":[280],"datasets":[281],"AGDN's":[283],"competitive":[284],"cross-dataset":[285],"adaptability,":[286],"particularly":[287],"F1-score,":[290],"supporting":[293],"its":[294],"applicability":[295],"inspection":[298],"scenarios.":[299]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}
