{"id":"https://openalex.org/W7125956513","doi":"https://doi.org/10.1109/smc58881.2025.11343179","title":"StrawDet-YOLO: A Real-Time and High Precision Object Detection for Strawberry","display_name":"StrawDet-YOLO: A Real-Time and High Precision Object Detection for Strawberry","publication_year":2025,"publication_date":"2025-10-05","ids":{"openalex":"https://openalex.org/W7125956513","doi":"https://doi.org/10.1109/smc58881.2025.11343179"},"language":null,"primary_location":{"id":"doi:10.1109/smc58881.2025.11343179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","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/A5124056264","display_name":"Yue Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yue Hu","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,International School,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,International School,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124131411","display_name":"Xiankun Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiankun Jiang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,International School,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,International School,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5123383741","display_name":"Jianfeng Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]},{"id":"https://openalex.org/I4392021250","display_name":"State Key Laboratory of Networking and Switching Technology","ror":"https://ror.org/00qtv5q45","country_code":null,"type":"facility","lineage":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Guan","raw_affiliation_strings":["Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications,State Key Laboratory of Networking and Switching Technology,Beijing,China,100876","institution_ids":["https://openalex.org/I139759216","https://openalex.org/I4392021250"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"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":"6791","last_page":"6797"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9824000000953674,"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":0.9824000000953674,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.003100000089034438,"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/T12660","display_name":"Plant Disease Management Techniques","score":0.002099999925121665,"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/object-detection","display_name":"Object detection","score":0.621399998664856},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5291000008583069},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.48179998993873596},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.45890000462532043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4507000148296356},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.44830000400543213},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44620001316070557},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.43549999594688416}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7376999855041504},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6662999987602234},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.621399998664856},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5291000008583069},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.48179998993873596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4616999924182892},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.45890000462532043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4507000148296356},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.44830000400543213},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44620001316070557},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.43549999594688416},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4336000084877014},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.42669999599456787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3799000084400177},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34630000591278076},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.34439998865127563},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34139999747276306},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.28290000557899475},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C135598885","wikidata":"https://www.wikidata.org/wiki/Q1366302","display_name":"Row","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.2578999996185303},{"id":"https://openalex.org/C2777904410","wikidata":"https://www.wikidata.org/wiki/Q7397","display_name":"Software","level":2,"score":0.2549999952316284}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smc58881.2025.11343179","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smc58881.2025.11343179","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Systems, Man, and Cybernetics (SMC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger","score":0.6993874907493591}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1536680647","https://openalex.org/W2102605133","https://openalex.org/W2109255472","https://openalex.org/W2570343428","https://openalex.org/W2963037989","https://openalex.org/W2963299996","https://openalex.org/W2963351448","https://openalex.org/W2963717374","https://openalex.org/W2982770724","https://openalex.org/W3012573144","https://openalex.org/W3107473354","https://openalex.org/W3196078976","https://openalex.org/W3204309289","https://openalex.org/W4211009416","https://openalex.org/W4320519943","https://openalex.org/W4386071462","https://openalex.org/W4390189829","https://openalex.org/W4392166384","https://openalex.org/W4407808502","https://openalex.org/W4408170571","https://openalex.org/W4408250502","https://openalex.org/W6947681574"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"detection":[1,16,37],"of":[2],"strawberry":[3,44],"diseases":[4],"is":[5],"critical":[6],"for":[7,43,84,98,160],"ensuring":[8],"yield":[9],"stability":[10],"and":[11,62,71,89,94,126,140,165],"fruit":[12],"quality,":[13],"yet":[14,35],"existing":[15],"methods":[17],"struggle":[18],"with":[19],"fine-grained":[20],"symptom":[21],"variations,":[22],"complex":[23],"field":[24],"conditions.":[25],"To":[26],"address":[27],"these":[28],"challenges,":[29],"we":[30,52,75,111],"propose":[31],"StrawDet-YOLO,":[32],"a":[33,55,113,136],"lightweight":[34],"high-precision":[36],"model":[38],"based":[39],"on":[40],"YOLOv8,":[41],"tailored":[42],"disease":[45,166],"recognition":[46],"in":[47,162],"real-world":[48],"agricultural":[49],"environments.":[50],"First,":[51],"construct":[53],"Strawberry-12,":[54],"new":[56],"benchmark":[57],"dataset":[58],"containing":[59],"3,906":[60],"images":[61],"16,107":[63],"annotations":[64],"across":[65],"12":[66],"categories,":[67],"including":[68],"diseases,":[69],"pests,":[70],"nutrient":[72],"deficiencies.":[73],"Second,":[74],"introduce":[76],"the":[77,90,104],"BFSA":[78],"(Bilinear":[79],"Fused":[80],"Synergic":[81],"Attention)":[82],"module":[83,97],"refined":[85],"spatial-channel":[86],"attention":[87],"fusion":[88],"R-SCConv":[91],"(Residual":[92],"Spatial":[93],"Channel":[95],"Convolution)":[96],"robust":[99],"multi-scale":[100],"feature":[101],"reconstruction,":[102],"improving":[103],"model\u2019s":[105],"sensitivity":[106],"to":[107,121,144],"subtle":[108],"lesions.":[109],"Finally,":[110],"design":[112],"gradient-aware":[114],"loss":[115],"function":[116],"GWIoU":[117],"(Gradient-Weighted":[118],"IoU":[119],"loss)":[120],"dynamically":[122],"emphasize":[123],"hard":[124],"samples":[125],"enhance":[127],"localization":[128],"performance.":[129],"Extensive":[130],"experiments":[131],"demonstrate":[132],"that":[133],"StrawDet-YOLO":[134],"achieves":[135],"7.7%":[137],"precision":[138],"improvement":[139],"superior":[141],"mAP":[142],"compared":[143],"YOLOv8n,":[145],"while":[146],"maintaining":[147],"real-time":[148],"inference":[149],"at":[150],"0.4":[151],"ms":[152],"per":[153],"image.":[154],"These":[155],"results":[156],"validate":[157],"its":[158],"practicality":[159],"deployment":[161],"smart":[163],"farming":[164],"monitoring":[167],"applications.":[168]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-01-29T00:00:00"}
