{"id":"https://openalex.org/W7166005650","doi":"https://doi.org/10.1007/s11760-026-05527-8","title":"EnCropNet: deep feature fusion with channel attention for accurate crop damage classification","display_name":"EnCropNet: deep feature fusion with channel attention for accurate crop damage classification","publication_year":2026,"publication_date":"2026-06-26","ids":{"openalex":"https://openalex.org/W7166005650","doi":"https://doi.org/10.1007/s11760-026-05527-8"},"language":"en","primary_location":{"id":"doi:10.1007/s11760-026-05527-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11760-026-05527-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11760-026-05527-8.pdf","source":{"id":"https://openalex.org/S156904493","display_name":"Signal Image and Video Processing","issn_l":"1863-1703","issn":["1863-1703","1863-1711"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Signal, Image and Video Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11760-026-05527-8.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125348151","display_name":"Amir Shahzad","orcid":null},"institutions":[{"id":"https://openalex.org/I146840658","display_name":"University of Azad Jammu and Kashmir","ror":"https://ror.org/015566d55","country_code":"PK","type":"education","lineage":["https://openalex.org/I146840658"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Amir Shahzad","raw_affiliation_strings":["Department of Computer Science and Information Technology, University of Poonch Rawalakot, Azad Jammu and Kashmir, RQWF+MQ4, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, University of Poonch Rawalakot, Azad Jammu and Kashmir, RQWF+MQ4, Pakistan","institution_ids":["https://openalex.org/I146840658"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125366163","display_name":"Anum Mushtaq","orcid":null},"institutions":[{"id":"https://openalex.org/I146840658","display_name":"University of Azad Jammu and Kashmir","ror":"https://ror.org/015566d55","country_code":"PK","type":"education","lineage":["https://openalex.org/I146840658"]}],"countries":["PK"],"is_corresponding":true,"raw_author_name":"Anum Mushtaq","raw_affiliation_strings":["Department of Computer Science and Information Technology, University of Poonch Rawalakot, Azad Jammu and Kashmir, RQWF+MQ4, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, University of Poonch Rawalakot, Azad Jammu and Kashmir, RQWF+MQ4, Pakistan","institution_ids":["https://openalex.org/I146840658"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008079276","display_name":"Jawad-ur-Rehman Chughtai","orcid":"https://orcid.org/0000-0003-0430-4661"},"institutions":[{"id":"https://openalex.org/I146840658","display_name":"University of Azad Jammu and Kashmir","ror":"https://ror.org/015566d55","country_code":"PK","type":"education","lineage":["https://openalex.org/I146840658"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Jawad-ur-Rehman Chughtai","raw_affiliation_strings":["Department of Computer Science and Information Technology, Women University of Azad Jammu and Kashmir Bagh, Bagh, 12500, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Technology, Women University of Azad Jammu and Kashmir Bagh, Bagh, 12500, Pakistan","institution_ids":["https://openalex.org/I146840658"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014155780","display_name":"Arslan Amjad","orcid":"https://orcid.org/0000-0002-6711-4382"},"institutions":[{"id":"https://openalex.org/I119004910","display_name":"Silesian University of Technology","ror":"https://ror.org/02dyjk442","country_code":"PL","type":"education","lineage":["https://openalex.org/I119004910"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Arslan Amjad","raw_affiliation_strings":["Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, Gliwice, 44-100, Poland"],"raw_orcid":"https://orcid.org/0000-0002-6711-4382","affiliations":[{"raw_affiliation_string":"Department of Computer Graphics, Vision and Digital Systems, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Akademicka 16, Gliwice, 44-100, Poland","institution_ids":["https://openalex.org/I119004910"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5014155780","https://openalex.org/A5125366163"],"corresponding_institution_ids":["https://openalex.org/I119004910","https://openalex.org/I146840658"],"apc_list":{"value":3390,"currency":"USD","value_usd":3390},"apc_paid":{"value":3390,"currency":"USD","value_usd":3390},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.61210074,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"8","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9470000267028809,"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":0.9470000267028809,"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/T12660","display_name":"Plant Disease Management Techniques","score":0.011500000022351742,"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/T12161","display_name":"Plant Surface Properties and Treatments","score":0.006500000134110451,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6510000228881836},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5156000256538391},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4790000021457672},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4465000033378601},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4293999969959259},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4262999892234802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.421999990940094},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.39899998903274536},{"id":"https://openalex.org/keywords/local-binary-patterns","display_name":"Local binary patterns","score":0.3822999894618988},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.3749000132083893}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193999886512756},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6510000228881836},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.590499997138977},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5156000256538391},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4790000021457672},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4377000033855438},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.421999990940094},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.39899998903274536},{"id":"https://openalex.org/C87335442","wikidata":"https://www.wikidata.org/wiki/Q2494345","display_name":"Local binary patterns","level":4,"score":0.3822999894618988},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3749000132083893},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.3747999966144562},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.35910001397132874},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3467999994754791},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.34360000491142273},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3070000112056732},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.30090001225471497},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2971000075340271},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.2955999970436096},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.295199990272522},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C107445234","wikidata":"https://www.wikidata.org/wiki/Q280995","display_name":"Panchromatic film","level":3,"score":0.28790000081062317},{"id":"https://openalex.org/C137580998","wikidata":"https://www.wikidata.org/wiki/Q235352","display_name":"Crop","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.26489999890327454},{"id":"https://openalex.org/C118518473","wikidata":"https://www.wikidata.org/wiki/Q11451","display_name":"Agriculture","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2533000111579895}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s11760-026-05527-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11760-026-05527-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11760-026-05527-8.pdf","source":{"id":"https://openalex.org/S156904493","display_name":"Signal Image and Video Processing","issn_l":"1863-1703","issn":["1863-1703","1863-1711"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Signal, Image and Video Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s11760-026-05527-8","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11760-026-05527-8","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11760-026-05527-8.pdf","source":{"id":"https://openalex.org/S156904493","display_name":"Signal Image and Video Processing","issn_l":"1863-1703","issn":["1863-1703","1863-1711"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Signal, Image and Video Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.5913233160972595,"display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7166005650.pdf","grobid_xml":"https://content.openalex.org/works/W7166005650.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1992021777","https://openalex.org/W2108598243","https://openalex.org/W2183341477","https://openalex.org/W2614850301","https://openalex.org/W2752782242","https://openalex.org/W2789255992","https://openalex.org/W2790979755","https://openalex.org/W2883780447","https://openalex.org/W2963163009","https://openalex.org/W2963446712","https://openalex.org/W2963995737","https://openalex.org/W3034429256","https://openalex.org/W3125895999","https://openalex.org/W4285193096","https://openalex.org/W4294252858","https://openalex.org/W4294325784","https://openalex.org/W4308391678","https://openalex.org/W4318570541","https://openalex.org/W4319984936","https://openalex.org/W4366606637","https://openalex.org/W4376139110","https://openalex.org/W4381487685","https://openalex.org/W4400026650","https://openalex.org/W4400557192","https://openalex.org/W4405585059","https://openalex.org/W4406930542","https://openalex.org/W4410506545"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"crop":[1,31,45,64,187],"damage":[2,32,42,65,188],"detection":[3],"is":[4,60,179],"vital":[5],"for":[6,62,95,185],"sustaining":[7],"agricultural":[8,193],"productivity":[9],"and":[10,47,103,131,147,162,182,201],"ensuring":[11],"food":[12],"security,":[13],"particularly":[14,190],"within":[15],"the":[16,28,75,110],"scope":[17],"of":[18,30,80,109,154],"precision":[19],"farming.":[20],"Despite":[21],"significant":[22],"advancements":[23],"in":[24,191],"Deep":[25],"Learning":[26],"(DL),":[27],"classification":[29,66],"under":[33],"diverse":[34],"real-world":[35],"conditions":[36],"remains":[37],"challenging":[38],"due":[39],"to":[40,167,203],"heterogeneous":[41],"patterns,":[43],"variable":[44],"types,":[46],"environmental":[48],"inconsistencies.":[49],"To":[50,119],"overcome":[51],"these":[52],"challenges,":[53],"a":[54,83,106,150],"hybrid":[55],"DL":[56],"framework":[57],"(i.e.,":[58],"EnCropNet)":[59],"proposed":[61,72,137],"binary":[63],"using":[67],"field-level":[68],"RGB":[69],"images.":[70],"The":[71,99,136,174],"model":[73,100,138],"integrates":[74],"global":[76],"semantic":[77],"representation":[78],"power":[79],"DenseNet121":[81],"with":[82],"lightweight":[84],"convolutional":[85],"stream":[86],"inspired":[87],"by":[88],"ShuffleNetV2,":[89,148],"enhanced":[90],"via":[91],"Squeeze-and-Excitation":[92],"(SE)":[93],"blocks":[94],"improved":[96],"channel-wise":[97],"attention.":[98],"was":[101],"trained":[102],"evaluated":[104],"on":[105],"balanced":[107],"version":[108],"publicly":[111],"available":[112],"CGIAR":[113],"Crop":[114],"Damage":[115],"Classification":[116],"(CDC)":[117],"dataset.":[118],"enhance":[120],"generalization,":[121],"extensive":[122],"augmentation":[123],"techniques":[124],"such":[125,159],"as":[126,160],"random":[127],"rotations,":[128],"brightness":[129],"variations,":[130],"zoom":[132],"transformations":[133],"were":[134],"applied.":[135],"outperformed":[139],"leading":[140],"baseline":[141],"models,":[142],"including":[143],"LightCDC,":[144],"DenseNet121,":[145],"EfficientNetV2S,":[146],"achieving":[149],"notable":[151],"test":[152],"accuracy":[153],"90.00%.":[155],"Additionally,":[156],"visualization":[157],"tools":[158],"GradCAM":[161],"t-SNE":[163],"confirm":[164],"EnCropNet":[165,178],"ability":[166],"capture":[168],"discriminative":[169],"features":[170],"while":[171],"maintaining":[172],"transparency.":[173],"results":[175],"suggest":[176],"that":[177],"an":[180],"effective":[181],"scalable":[183],"solution":[184],"real-time":[186],"assessment,":[189],"low-resource":[192],"environments.":[194],"Its":[195],"deployment":[196],"could":[197],"support":[198],"timely":[199],"decision-making":[200],"contribute":[202],"sustainable":[204],"farming":[205],"practices.":[206]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-06-27T00:00:00"}
