{"id":"https://openalex.org/W4226162220","doi":"https://doi.org/10.1145/3498851.3498948","title":"A Method for Recognizing and Counting Residual Bait of Penaeus Vannamei Based on Deep Learning","display_name":"A Method for Recognizing and Counting Residual Bait of Penaeus Vannamei Based on Deep Learning","publication_year":2021,"publication_date":"2021-12-14","ids":{"openalex":"https://openalex.org/W4226162220","doi":"https://doi.org/10.1145/3498851.3498948"},"language":"en","primary_location":{"id":"doi:10.1145/3498851.3498948","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3498851.3498948","pdf_url":null,"source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC/ACM International Conference on Web Intelligence","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/A5055983271","display_name":"Chuting Yu","orcid":"https://orcid.org/0000-0001-8299-427X"},"institutions":[{"id":"https://openalex.org/I165143802","display_name":"The University of Queensland","ror":"https://ror.org/00rqy9422","country_code":"AU","type":"education","lineage":["https://openalex.org/I165143802"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chuting Yu","raw_affiliation_strings":["The University of Queensland Brisbane Queensland Australia, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Queensland Brisbane Queensland Australia, Australia","institution_ids":["https://openalex.org/I165143802"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100345851","display_name":"Yu Li","orcid":"https://orcid.org/0000-0002-8411-1394"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Li","raw_affiliation_strings":["NingboTech University Ningbo Zhejiang China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NingboTech University Ningbo Zhejiang China, China","institution_ids":["https://openalex.org/I159389169"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101860598","display_name":"Xinjie Yu","orcid":"https://orcid.org/0000-0002-6462-3931"},"institutions":[{"id":"https://openalex.org/I159389169","display_name":"Ningbo University of Technology","ror":"https://ror.org/037dym702","country_code":"CN","type":"education","lineage":["https://openalex.org/I159389169"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinjie Yu","raw_affiliation_strings":["NingboTech University Ningbo Zhejiang China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NingboTech University Ningbo Zhejiang China, China","institution_ids":["https://openalex.org/I159389169"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3821,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5471246,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"176","last_page":"183"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10450","display_name":"Aquaculture Nutrition and Growth","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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/T12319","display_name":"Fish Biology and Ecology Studies","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1104","display_name":"Aquatic 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/residual","display_name":"Residual","score":0.8067898750305176},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7487224340438843},{"id":"https://openalex.org/keywords/prawn","display_name":"Prawn","score":0.7358789443969727},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6860924363136292},{"id":"https://openalex.org/keywords/shrimp","display_name":"Shrimp","score":0.6278253197669983},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6070543527603149},{"id":"https://openalex.org/keywords/penaeus","display_name":"Penaeus","score":0.5565191507339478},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5132327079772949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4954639673233032},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35513365268707275},{"id":"https://openalex.org/keywords/fishery","display_name":"Fishery","score":0.19760337471961975},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11231955885887146},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0904591977596283}],"concepts":[{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.8067898750305176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7487224340438843},{"id":"https://openalex.org/C2776115401","wikidata":"https://www.wikidata.org/wiki/Q1058410","display_name":"Prawn","level":2,"score":0.7358789443969727},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6860924363136292},{"id":"https://openalex.org/C2776841996","wikidata":"https://www.wikidata.org/wiki/Q1517781","display_name":"Shrimp","level":2,"score":0.6278253197669983},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6070543527603149},{"id":"https://openalex.org/C2776599375","wikidata":"https://www.wikidata.org/wiki/Q3011709","display_name":"Penaeus","level":3,"score":0.5565191507339478},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5132327079772949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4954639673233032},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35513365268707275},{"id":"https://openalex.org/C505870484","wikidata":"https://www.wikidata.org/wiki/Q180538","display_name":"Fishery","level":1,"score":0.19760337471961975},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11231955885887146},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0904591977596283}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3498851.3498948","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3498851.3498948","pdf_url":null,"source":{"id":"https://openalex.org/S4363608074","display_name":"IEEE/WIC/ACM International Conference on Web Intelligence","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE/WIC/ACM International Conference on Web Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2105816476","https://openalex.org/W2589255103","https://openalex.org/W3048971535"],"related_works":["https://openalex.org/W3090796741","https://openalex.org/W2349459666","https://openalex.org/W2330307498","https://openalex.org/W2010171561","https://openalex.org/W1987459813","https://openalex.org/W4384297484","https://openalex.org/W2071067837","https://openalex.org/W2615966921","https://openalex.org/W2041181100","https://openalex.org/W2065476624"],"abstract_inverted_index":{"This":[0,182],"research":[1],"has":[2,84],"developed":[3],"a":[4,15,19,65,90,98,185],"neural":[5],"network":[6],"model":[7,83,140],"based":[8],"on":[9],"deep":[10,156],"learning,":[11],"which":[12],"consists":[13],"of":[14,55,72,95,103,193],"recognition":[16,23,87,92,100],"part":[17,24,36],"and":[18,34,60,64,97,142,162,169,172,196],"counting":[20,106],"part.":[21],"The":[22,123,128],"is":[25,37],"realized":[26,38],"by":[27,39],"the":[28,40,52,57,61,70,73,81,107,110,116,138,143,155,159,163,179,189],"Fully":[29],"Convolutional":[30],"Neural":[31],"Network":[32],"(FCN),":[33],"thecounting":[35],"NAS-CNN":[41,139],"model.":[42],"Labelme":[43],"(online":[44],"labeling":[45,112],"tool)":[46],"was":[47,76],"used":[48],"to":[49,200],"manually":[50],"mark":[51],"two":[53],"types":[54],"targets,":[56],"remnant":[58],"bait":[59,134,165,174],"white":[62,74,160],"prawn,":[63],"special":[66],"data":[67],"set":[68],"for":[69,115,187],"identification":[71],"prawn":[75],"created.":[77],"Experiments":[78],"show":[79],"that":[80,152],"FCN":[82],"achieved":[85],"excellent":[86],"results,":[88],"with":[89,118,130,154],"training":[91],"accuracy":[93,101,124,145],"rate":[94,102,125,146],"99%,":[96],"verification":[99,144],"96.13%.":[104],"When":[105],"residual":[108,121,133,164],"bait,":[109],"connected-component":[111],"(CCL)":[113],"isused":[114],"image":[117],"only":[119],"sporadic":[120],"bait.":[122],"reached":[126],"97.5%.":[127],"pictures":[129],"severe":[131],"adhesion":[132],"are":[135],"counted":[136,177],"using":[137],"training,":[141],"can":[147,166,175,197],"reach":[148],"88.52%.Experiments":[149],"have":[150],"proved":[151],"combined":[153],"learning":[157],"method,":[158],"shrimp":[161],"be":[167,176,198],"quickly":[168],"accurately":[170],"identified":[171],"theresidual":[173],"at":[178],"same":[180],"time.":[181],"method":[183],"provides":[184],"reference":[186],"exploring":[188],"scientific":[190],"breeding":[191],"methods":[192],"Penaeus":[194],"vannamei,":[195],"extended":[199],"use":[201],"in":[202],"other":[203],"aquaculture":[204],"environments.":[205]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}