{"id":"https://openalex.org/W3040635677","doi":"https://doi.org/10.1145/3403746.3403921","title":"An Animal Behavior State Estimation Method Using CCNN and BN Based System","display_name":"An Animal Behavior State Estimation Method Using CCNN and BN Based System","publication_year":2020,"publication_date":"2020-05-22","ids":{"openalex":"https://openalex.org/W3040635677","doi":"https://doi.org/10.1145/3403746.3403921","mag":"3040635677"},"language":"en","primary_location":{"id":"doi:10.1145/3403746.3403921","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3403746.3403921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Computer Science and Software Engineering","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/A5100448610","display_name":"Rui Li","orcid":"https://orcid.org/0000-0003-1770-906X"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Li","raw_affiliation_strings":["School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China","institution_ids":["https://openalex.org/I22716506"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103162015","display_name":"Yu Ren","orcid":"https://orcid.org/0009-0009-4929-6221"},"institutions":[{"id":"https://openalex.org/I22716506","display_name":"Lanzhou University of Technology","ror":"https://ror.org/03panb555","country_code":"CN","type":"education","lineage":["https://openalex.org/I22716506"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yu Ren","raw_affiliation_strings":["School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China","institution_ids":["https://openalex.org/I22716506"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2312,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.68668004,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"39","issue":null,"first_page":"158","last_page":"163"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9265999794006348,"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":0.9265999794006348,"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/computer-science","display_name":"Computer science","score":0.7926440834999084},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7153288125991821},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449779272079468},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.574038028717041},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5214701890945435},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.5170981884002686},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48239266872406006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4738907217979431},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4614250957965851},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.44418424367904663},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.44353994727134705},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4369765520095825},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08293959498405457}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7926440834999084},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7153288125991821},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449779272079468},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.574038028717041},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5214701890945435},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.5170981884002686},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48239266872406006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4738907217979431},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4614250957965851},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.44418424367904663},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.44353994727134705},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4369765520095825},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08293959498405457},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3403746.3403921","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3403746.3403921","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 3rd International Conference on Computer Science and Software Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land","score":0.6200000047683716}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2116273573","https://openalex.org/W2153149612","https://openalex.org/W2153659092","https://openalex.org/W2782689936","https://openalex.org/W2908260209","https://openalex.org/W2914978454","https://openalex.org/W2947469701","https://openalex.org/W2952113774","https://openalex.org/W2962019823","https://openalex.org/W2963226402","https://openalex.org/W2990943996","https://openalex.org/W3171383491"],"related_works":["https://openalex.org/W2153719181","https://openalex.org/W1971748923","https://openalex.org/W1566155057","https://openalex.org/W2060986072","https://openalex.org/W2052574922","https://openalex.org/W64588465","https://openalex.org/W3120641340","https://openalex.org/W2117825986","https://openalex.org/W3134067061","https://openalex.org/W2079855347"],"abstract_inverted_index":{"The":[0],"study":[1],"of":[2,41,49,88,105,125,154,164],"animal":[3,42,127],"behavior":[4,128,165],"can":[5],"provide":[6],"a":[7,56,114],"basis":[8],"for":[9,85],"ecological":[10,20],"researchers":[11,54],"to":[12,38,82,98],"help":[13],"them":[14],"formulate":[15],"more":[16,141],"reasonable":[17],"and":[18,100,134,144,161],"targeted":[19],"protection":[21],"strategies.":[22],"In":[23,80],"this":[24,93,138,149],"paper,":[25],"the":[26,39,46,53,74,86,103,110,118,122,126,152],"feature":[27,159],"detection":[28,40],"method":[29,112,130,150],"based":[30,131],"on":[31,109,113,132],"cascade":[32,57],"convolutional":[33,50,58,70],"neural":[34,51,59,89],"network":[35,60,90,97],"is":[36,140],"applied":[37],"features.":[43,106],"By":[44],"analyzing":[45],"general":[47,147],"flow":[48],"networks,":[52,71],"designed":[55],"with":[61,146],"three":[62],"hierarchical":[63,66],"structures.":[64],"Each":[65],"structure":[67],"has":[68,151],"multiple":[69],"which":[72],"perform":[73],"same":[75],"or":[76],"different":[77],"operations":[78],"respectively.":[79],"order":[81],"make":[83],"up":[84],"defects":[87],"in":[91,102,137],"reasoning,":[92],"paper":[94,139],"uses":[95],"Bayesian":[96],"infer":[99],"estimate":[101],"analysis":[104],"Through":[107],"experiments":[108],"proposed":[111,136],"self-built":[115],"data":[116],"set,":[117],"results":[119],"show":[120],"that":[121],"overall":[123],"accuracy":[124,163],"estimation":[129],"CCNN":[133],"BN":[135],"than":[142],"85%,":[143],"compared":[145],"methods,":[148],"advantages":[153],"fast":[155],"learning":[156],"speed,":[157],"accurate":[158],"location,":[160],"high":[162],"estimation.":[166]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}