{"id":"https://openalex.org/W7129254017","doi":"https://doi.org/10.1109/icipw68931.2025.11386377","title":"A Model-Agnostic Active Learning Approach For Animal Detection From Camera Traps","display_name":"A Model-Agnostic Active Learning Approach For Animal Detection From Camera Traps","publication_year":2025,"publication_date":"2025-09-14","ids":{"openalex":"https://openalex.org/W7129254017","doi":"https://doi.org/10.1109/icipw68931.2025.11386377"},"language":null,"primary_location":{"id":"doi:10.1109/icipw68931.2025.11386377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icipw68931.2025.11386377","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 Image Processing Workshops (ICIPW)","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/A5106232743","display_name":"Thi Thu Thuy Nguyen","orcid":"https://orcid.org/0009-0001-5125-3396"},"institutions":[{"id":"https://openalex.org/I4210107658","display_name":"Machine Intelligence Research Labs","ror":"https://ror.org/013kgb629","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210107658"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thi Thu Thuy Nguyen","raw_affiliation_strings":["Deakin University,Machine Intelligence Lab, School of Information Technology"],"affiliations":[{"raw_affiliation_string":"Deakin University,Machine Intelligence Lab, School of Information Technology","institution_ids":["https://openalex.org/I4210107658"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5024634557","display_name":"Duc Thanh Nguyen","orcid":"https://orcid.org/0000-0002-2285-2066"},"institutions":[{"id":"https://openalex.org/I4210107658","display_name":"Machine Intelligence Research Labs","ror":"https://ror.org/013kgb629","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210107658"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Duc Thanh Nguyen","raw_affiliation_strings":["Deakin University,Machine Intelligence Lab, School of Information Technology"],"affiliations":[{"raw_affiliation_string":"Deakin University,Machine Intelligence Lab, School of Information Technology","institution_ids":["https://openalex.org/I4210107658"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5106232743"],"corresponding_institution_ids":["https://openalex.org/I4210107658"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88237611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"598","last_page":"603"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.3375999927520752,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12072","display_name":"Machine Learning and Algorithms","score":0.3375999927520752,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10895","display_name":"Species Distribution and Climate Change","score":0.1340000033378601,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.06840000301599503,"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/active-learning","display_name":"Active learning (machine learning)","score":0.798799991607666},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.60589998960495},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5146999955177307},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4318000078201294},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4287000000476837},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4129999876022339},{"id":"https://openalex.org/keywords/active-vision","display_name":"Active vision","score":0.3578000068664551},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.35339999198913574},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3188999891281128}],"concepts":[{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.798799991607666},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7013000249862671},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6798999905586243},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6583999991416931},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.60589998960495},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5146999955177307},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4318000078201294},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4287000000476837},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4129999876022339},{"id":"https://openalex.org/C193611912","wikidata":"https://www.wikidata.org/wiki/Q4677596","display_name":"Active vision","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.35339999198913574},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.30889999866485596},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.27950000762939453},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.2752000093460083},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.2680000066757202},{"id":"https://openalex.org/C127757376","wikidata":"https://www.wikidata.org/wiki/Q2056514","display_name":"Active safety","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C163985040","wikidata":"https://www.wikidata.org/wiki/Q1172399","display_name":"Data acquisition","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C2776196576","wikidata":"https://www.wikidata.org/wiki/Q196113","display_name":"Camouflage","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icipw68931.2025.11386377","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icipw68931.2025.11386377","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 Image Processing Workshops (ICIPW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5764930248260498,"id":"https://metadata.un.org/sdg/15","display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2570343428","https://openalex.org/W2769210209","https://openalex.org/W2964340375","https://openalex.org/W3093414036","https://openalex.org/W3176659256","https://openalex.org/W4230013745","https://openalex.org/W4312407813","https://openalex.org/W4312795512","https://openalex.org/W4387020916","https://openalex.org/W4397007562","https://openalex.org/W4398250170","https://openalex.org/W4402753992","https://openalex.org/W4402915459","https://openalex.org/W4408494000"],"related_works":[],"abstract_inverted_index":{"Smart":[0],"data":[1,28,38,51,68,165],"selection":[2,144],"is":[3],"becoming":[4],"increasingly":[5],"important":[6],"in":[7,45,50,74,150],"data-driven":[8],"machine":[9,19,89],"learning.":[10],"Active":[11],"learning":[12,20,61,84,90,113,142],"offers":[13],"a":[14,71,88,110,151,170,176],"promising":[15],"solution":[16],"by":[17,40,120,167],"allowing":[18],"models":[21,56],"to":[22,62],"be":[23,70,96],"effectively":[24],"trained":[25],"with":[26,184],"optimal":[27],"including":[29],"the":[30,64,100,103,134,140,163,185,188],"most":[31],"informative":[32],"samples":[33,131],"from":[34],"large":[35],"datasets.":[36],"Wildlife":[37],"captured":[39,119],"camera":[41,121],"traps":[42],"are":[43],"excessive":[44],"volume,":[46],"requiring":[47],"tremendous":[48],"effort":[49],"labelling":[52],"and":[53,79,127,136],"animal":[54,153,172],"detection":[55,116],"training.":[57],"Therefore,":[58],"applying":[59],"active":[60,83,112,141],"optimise":[63],"amount":[65],"of":[66,102,117,130,162,178,187],"labelled":[67],"would":[69],"great":[72],"aid":[73],"enabling":[75],"automated":[76],"wildlife":[77],"monitoring":[78],"conservation.":[80],"However,":[81],"existing":[82],"techniques":[85],"require":[86],"that":[87,183],"model":[91],"(i.e.,":[92],"an":[93],"object":[94],"detector)":[95],"fully":[97],"accessible,":[98],"limiting":[99],"applicability":[101],"techniques.":[104],"In":[105],"this":[106],"paper,":[107],"we":[108],"propose":[109],"model-agnostic":[111],"approach":[114,124,149],"for":[115],"animals":[118],"traps.":[122],"Our":[123],"integrates":[125],"uncertainty":[126],"diversity":[128],"quantities":[129],"at":[132],"both":[133],"object-based":[135],"image-based":[137],"levels":[138],"into":[139],"sample":[143],"process.":[145],"We":[146],"validate":[147],"our":[148,168],"benchmark":[152],"dataset.":[154,191],"Experimental":[155],"results":[156],"demonstrate":[157],"that,":[158],"using":[159],"only":[160],"30%":[161],"training":[164,190],"selected":[166],"approach,":[169],"state-of-the-art":[171],"detector":[173],"can":[174],"achieve":[175],"performance":[177],"equal":[179],"or":[180],"greater":[181],"than":[182],"use":[186],"complete":[189]},"counts_by_year":[],"updated_date":"2026-02-19T06:27:42.648592","created_date":"2026-02-18T00:00:00"}