{"id":"https://openalex.org/W4399257659","doi":"https://doi.org/10.1145/3653804.3656269","title":"Research and Application of Lightweight Kiwifruit Recognition Based on Yolov5s","display_name":"Research and Application of Lightweight Kiwifruit Recognition Based on Yolov5s","publication_year":2024,"publication_date":"2024-01-19","ids":{"openalex":"https://openalex.org/W4399257659","doi":"https://doi.org/10.1145/3653804.3656269"},"language":"en","primary_location":{"id":"doi:10.1145/3653804.3656269","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653804.3656269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Computer Vision and Deep Learning","raw_type":"proceedings-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/A5102005206","display_name":"Jiaming Zhang","orcid":"https://orcid.org/0009-0007-7239-5442"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiaming Zhang","raw_affiliation_strings":["School of Computer Science, Zhongyuan University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0007-7239-5442","affiliations":[{"raw_affiliation_string":"School of Computer Science, Zhongyuan University of Technology, China","institution_ids":["https://openalex.org/I132586189"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5098972496","display_name":"Zanxia Qiang","orcid":"https://orcid.org/0009-0009-3146-9251"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zanxia Qiang","raw_affiliation_strings":["School of Computer Science, Zhongyuan University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0009-3146-9251","affiliations":[{"raw_affiliation_string":"School of Computer Science, Zhongyuan University of Technology, China","institution_ids":["https://openalex.org/I132586189"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023284929","display_name":"Yugang Li","orcid":"https://orcid.org/0009-0005-0339-1347"},"institutions":[{"id":"https://openalex.org/I132586189","display_name":"Zhongyuan University of Technology","ror":"https://ror.org/0360zcg91","country_code":"CN","type":"education","lineage":["https://openalex.org/I132586189"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yugang Li","raw_affiliation_strings":["School of Computer Science, Zhongyuan University of Technology, China"],"raw_orcid":"https://orcid.org/0009-0005-0339-1347","affiliations":[{"raw_affiliation_string":"School of Computer Science, Zhongyuan University of Technology, China","institution_ids":["https://openalex.org/I132586189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102005206"],"corresponding_institution_ids":["https://openalex.org/I132586189"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04134647,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9969000220298767,"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":0.9969000220298767,"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/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.9753999710083008,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13890","display_name":"Remote Sensing and Land Use","score":0.9613000154495239,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6527681350708008},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5931076407432556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5169922113418579},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4912347197532654},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47048619389533997},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3445638418197632},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11629170179367065}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6527681350708008},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5931076407432556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5169922113418579},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4912347197532654},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47048619389533997},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3445638418197632},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11629170179367065},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653804.3656269","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3653804.3656269","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Computer Vision and Deep Learning","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W3018757597","https://openalex.org/W3129818014","https://openalex.org/W3138516171","https://openalex.org/W3159196909","https://openalex.org/W3184439416","https://openalex.org/W4285008339","https://openalex.org/W4301045096","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398","https://openalex.org/W2775347418"],"abstract_inverted_index":{"In":[0],"response":[1],"to":[2,31,51,80,100],"the":[3,35,40,68,83,89],"issues":[4],"of":[5,34,75,88],"large":[6],"model":[7,71,92],"size":[8,87],"in":[9],"current":[10],"automatic":[11],"detection":[12],"and":[13,46,86,97],"recognition":[14],"methods":[15],"for":[16],"kiwifruits,":[17],"a":[18,61],"novel":[19],"lightweight":[20],"network":[21,37,70,91],"model,":[22],"Yolov5s-GST,":[23],"is":[24],"proposed.":[25],"Firstly,":[26],"Ghost":[27],"modules":[28],"are":[29,49,93],"employed":[30],"replace":[32],"part":[33],"Yolov5s":[36],"modules.":[38],"Secondly,":[39],"computationally":[41],"demanding":[42],"SE":[43],"attention":[44],"mechanism":[45],"Transformer":[47],"module":[48],"introduced":[50],"extract":[52],"multi-dimensional":[53],"feature":[54],"information":[55],"from":[56],"images.":[57],"Experimental":[58],"results":[59],"on":[60],"kiwi":[62],"fruit":[63],"image":[64],"dataset":[65],"demonstrate":[66],"that":[67],"Yolov5s-GST":[69,90],"achieves":[72],"an":[73],"AP50-95":[74],"87.1%,":[76],"improving":[77],"0.7%":[78],"compared":[79,99],"Yolov5s.":[81,101],"Furthermore,":[82],"parameter":[84],"count":[85],"reduced":[94],"by":[95],"44%":[96],"43%":[98]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}