{"id":"https://openalex.org/W2937645975","doi":"https://doi.org/10.1145/3314545.3314559","title":"Automatically Identifying of animals in the wilderness","display_name":"Automatically Identifying of animals in the wilderness","publication_year":2019,"publication_date":"2019-03-14","ids":{"openalex":"https://openalex.org/W2937645975","doi":"https://doi.org/10.1145/3314545.3314559","mag":"2937645975"},"language":"en","primary_location":{"id":"doi:10.1145/3314545.3314559","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3314545.3314559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Compute and Data Analysis","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/A5090335546","display_name":"Joel Kamdem Teto","orcid":null},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Joel Kamdem Teto","raw_affiliation_strings":["Kennesaw State University, Marietta, Ga"],"affiliations":[{"raw_affiliation_string":"Kennesaw State University, Marietta, Ga","institution_ids":["https://openalex.org/I172980758"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101628906","display_name":"Ying Xie","orcid":"https://orcid.org/0000-0002-6419-3986"},"institutions":[{"id":"https://openalex.org/I172980758","display_name":"Kennesaw State University","ror":"https://ror.org/00jeqjx33","country_code":"US","type":"education","lineage":["https://openalex.org/I172980758"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ying Xie","raw_affiliation_strings":["Kennesaw State University Department of Information Technology, Kennesaw, GA"],"affiliations":[{"raw_affiliation_string":"Kennesaw State University Department of Information Technology, Kennesaw, GA","institution_ids":["https://openalex.org/I172980758"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5090335546"],"corresponding_institution_ids":["https://openalex.org/I172980758"],"apc_list":null,"apc_paid":null,"fwci":0.2024,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.51630886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"128","last_page":"133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9990000128746033,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9986000061035156,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9979000091552734,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6928139328956604},{"id":"https://openalex.org/keywords/wilderness","display_name":"Wilderness","score":0.6836010217666626},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6568392515182495},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.636791467666626},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5975014567375183},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5738169550895691},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5724326372146606},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5510091781616211},{"id":"https://openalex.org/keywords/wilderness-area","display_name":"Wilderness area","score":0.4859431982040405},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4274364113807678},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4198282063007355},{"id":"https://openalex.org/keywords/malware","display_name":"Malware","score":0.4153795540332794},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2120971381664276},{"id":"https://openalex.org/keywords/management","display_name":"Management","score":0.15500763058662415},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1529587209224701},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.1398366391658783}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6928139328956604},{"id":"https://openalex.org/C2778677346","wikidata":"https://www.wikidata.org/wiki/Q911871","display_name":"Wilderness","level":2,"score":0.6836010217666626},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6568392515182495},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.636791467666626},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5975014567375183},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5738169550895691},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5724326372146606},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5510091781616211},{"id":"https://openalex.org/C169013144","wikidata":"https://www.wikidata.org/wiki/Q2445527","display_name":"Wilderness area","level":3,"score":0.4859431982040405},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4274364113807678},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4198282063007355},{"id":"https://openalex.org/C541664917","wikidata":"https://www.wikidata.org/wiki/Q14001","display_name":"Malware","level":2,"score":0.4153795540332794},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2120971381664276},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.15500763058662415},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1529587209224701},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.1398366391658783},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3314545.3314559","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3314545.3314559","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2019 3rd International Conference on Compute and Data Analysis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320290","display_name":"University of Oxford","ror":"https://ror.org/052gg0110"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2097117768","https://openalex.org/W2101474437","https://openalex.org/W2162950292","https://openalex.org/W2183341477","https://openalex.org/W2560763730","https://openalex.org/W2618530766","https://openalex.org/W2775143585","https://openalex.org/W2789257191","https://openalex.org/W2798515522","https://openalex.org/W2805939409","https://openalex.org/W2884367402","https://openalex.org/W2973651390","https://openalex.org/W2997574889"],"related_works":["https://openalex.org/W2071226361","https://openalex.org/W1977641836","https://openalex.org/W2084218260","https://openalex.org/W2090833528","https://openalex.org/W2911220673","https://openalex.org/W2962503459","https://openalex.org/W2419173517","https://openalex.org/W2285440879","https://openalex.org/W1577968875","https://openalex.org/W2331274460"],"abstract_inverted_index":{"The":[0],"evolution":[1],"of":[2,14,56,62,93,104,180,266],"machine":[3,47],"learning":[4,134,165,191],"and":[5,16,37,59,129,138,196,223],"computer":[6],"vision":[7],"in":[8,65],"technology":[9],"has":[10],"driven":[11],"a":[12,91,102,185,197,218,228,254,270],"lot":[13],"improvements":[15],"innovation":[17],"into":[18,79],"several":[19],"domains.":[20],"We":[21,202,233],"see":[22],"it":[23],"being":[24],"applied":[25],"for":[26,118,145],"credit":[27],"decisions,":[28],"insurance":[29],"quotes,":[30],"malware":[31],"detection,":[32,34],"fraud":[33],"email":[35],"composition,":[36],"any":[38],"other":[39],"area":[40],"having":[41],"enough":[42],"information":[43],"to":[44,48,75,108,124,155,162,177,183,248],"allow":[45],"the":[46,52,54,66,73,86,114,141,146,163,169,207,240,263],"learn":[49],"patterns.":[50],"Over":[51],"years":[53],"number":[55],"sensors,":[57],"cameras":[58],"cognitive":[60],"pieces":[61],"equipment":[63],"placed":[64],"wilderness":[67],"have":[68],"been":[69],"growing":[70],"exponentially.":[71],"However,":[72],"resources(human)":[74],"leverage":[76],"these":[77,181],"data":[78,182],"something":[80],"meaningful":[81],"are":[82,122,175],"not":[83],"improving":[84],"at":[85,101],"same":[87,147,241],"rate.":[88],"For":[89],"instance,":[90],"team":[92],"scientist":[94],"volunteers":[95],"took":[96],"8.4":[97],"years,":[98],"17000":[99],"hours":[100],"rate":[103],"40":[105],"hours/":[106],"week":[107],"label":[109],"3.2":[110],"million":[111],"images":[112],"from":[113,273],"Serengeti":[115,208],"wild":[116,127],"park":[117],"our":[119,204],"research,":[120],"we":[121,174,245],"going":[123,176],"focus":[125],"on":[126,188,239,253,269],"data,":[128],"keep":[130],"proving":[131],"that":[132],"deep":[133,164],"can":[135],"do":[136],"better":[137],"faster":[139],"than":[140],"human":[142],"equivalent":[143],"labour":[144],"task.":[148,243],"Moreover,":[149],"this":[150],"is":[151],"also":[152],"an":[153],"opportunity":[154],"present":[156],"some":[157],"custom":[158,198],"Capsule":[159,267],"Networks":[160],"architectures":[161],"community":[166],"while":[167],"solving":[168],"above-mentioned":[170],"critical":[171],"problem.":[172],"Incidentally,":[173],"take":[178],"advantage":[179],"make":[184],"comparative":[186],"study":[187],"multiple":[189],"Deep":[190],"models.":[192],"Specifically,":[193],"VGG-net,":[194],"RES-net":[195],"made":[199],"Convolutional-Capsule":[200],"Network.":[201],"benchmark":[203],"work":[205],"with":[206,278],"project":[209],"where":[210],"Mohammed":[211,212],"Sadegh":[213],"et":[214,225,276],"al.":[215,226,277],"recently":[216],"published":[217],"92%":[219],"top-1":[220,230,237,250],"accuracy":[221,231,238,252,281],"[15]":[222],"Gomez":[224],"had":[227],"58%":[229],"[8].":[232],"successfully":[234],"reached":[235],"96.4%":[236],"identification":[242],"Concurrently,":[244],"reach":[246],"up":[247],"79.48%":[249],"testing":[251,280],"big":[255],"complex":[256,271],"dataset":[257,272],"using":[258],"capsule":[259],"network,":[260],"which":[261],"out-perform":[262],"best":[264],"results":[265],"networks":[268],"Edgar":[274],"Xi":[275],"71%":[279],"[5,23,18].":[282]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
