{"id":"https://openalex.org/W2725546079","doi":"https://doi.org/10.1109/inista.2017.8001185","title":"Operational data augmentation in classifying single aerial images of animals","display_name":"Operational data augmentation in classifying single aerial images of animals","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2725546079","doi":"https://doi.org/10.1109/inista.2017.8001185","mag":"2725546079"},"language":"en","primary_location":{"id":"doi:10.1109/inista.2017.8001185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista.2017.8001185","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pure.rug.nl/ws/files/44147232/64071.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5014716134","display_name":"Emmanuel Okafor","orcid":"https://orcid.org/0000-0001-6929-6880"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":true,"raw_author_name":"Emmanuel Okafor","raw_affiliation_strings":["Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039852925","display_name":"Rik Smit","orcid":"https://orcid.org/0000-0002-9235-6869"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Rik Smit","raw_affiliation_strings":["Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028858025","display_name":"Lambert Schomaker","orcid":"https://orcid.org/0000-0003-2351-930X"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Lambert Schomaker","raw_affiliation_strings":["Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060596453","display_name":"Marco Wiering","orcid":"https://orcid.org/0000-0003-4331-7537"},"institutions":[{"id":"https://openalex.org/I169381384","display_name":"University of Groningen","ror":"https://ror.org/012p63287","country_code":"NL","type":"education","lineage":["https://openalex.org/I169381384"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Marco Wiering","raw_affiliation_strings":["Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands"],"affiliations":[{"raw_affiliation_string":"Institute of Artificial Intelligence and Cognitive Engineering, University of Groningen, The Netherlands","institution_ids":["https://openalex.org/I169381384"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014716134"],"corresponding_institution_ids":["https://openalex.org/I169381384"],"apc_list":null,"apc_paid":null,"fwci":1.4788,"has_fulltext":false,"cited_by_count":37,"citation_normalized_percentile":{"value":0.89494378,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"354","last_page":"360"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9900000095367432,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9900000095367432,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9781000018119812,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9769999980926514,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8145848512649536},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7402995824813843},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6278682947158813},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5825188755989075},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.5569552183151245},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.538196861743927},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5229367017745972},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4408811032772064},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4311109781265259},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.42662322521209717},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36401310563087463}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8145848512649536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7402995824813843},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6278682947158813},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5825188755989075},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.5569552183151245},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.538196861743927},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5229367017745972},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4408811032772064},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4311109781265259},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.42662322521209717},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36401310563087463}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/inista.2017.8001185","is_oa":false,"landing_page_url":"https://doi.org/10.1109/inista.2017.8001185","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.rug.nl:publications/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","pdf_url":"https://pure.rug.nl/ws/files/44147232/64071.pdf","source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Okafor, E, Smit, R, Schomaker, L & Wiering, M 2017, Operational Data Augmentation in Classifying Single Aerial Images of Animals. in IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017. IEEE, pp. 354-360, IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017, Gdynia, Poland, 03/07/2017. https://doi.org/10.1109/INISTA.2017.8001185","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.rug.nl:openaire_cris_publications/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","is_oa":true,"landing_page_url":"https://hdl.handle.net/11370/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","pdf_url":null,"source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Okafor, E, Smit, R, Schomaker, L & Wiering, M 2017, Operational Data Augmentation in Classifying Single Aerial Images of Animals. in IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017. IEEE, pp. 354-360, IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017, Gdynia, Poland, 03/07/2017. https://doi.org/10.1109/INISTA.2017.8001185","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"pmh:oai:pure.rug.nl:publications/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","is_oa":true,"landing_page_url":"https://research.rug.nl/en/publications/a65cbc33-bff8-4c5e-9f55-e3ae774ef713","pdf_url":"https://pure.rug.nl/ws/files/44147232/64071.pdf","source":{"id":"https://openalex.org/S4306400420","display_name":"University of Groningen research database (University of Groningen / Centre for Information Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I169381384","host_organization_name":"University of Groningen","host_organization_lineage":["https://openalex.org/I169381384"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Okafor, E, Smit, R, Schomaker, L & Wiering, M 2017, Operational Data Augmentation in Classifying Single Aerial Images of Animals. in IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017. IEEE, pp. 354-360, IEEE International Conference on INnovations in Intelligent SysTems and Applications (INISTA), 2017, Gdynia, Poland, 03/07/2017. https://doi.org/10.1109/INISTA.2017.8001185","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2725546079.pdf"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W30160346","https://openalex.org/W104184427","https://openalex.org/W1200922351","https://openalex.org/W1946093182","https://openalex.org/W2074464158","https://openalex.org/W2097117768","https://openalex.org/W2132254548","https://openalex.org/W2161969291","https://openalex.org/W2179488730","https://openalex.org/W2236370645","https://openalex.org/W2253429366","https://openalex.org/W2467838519","https://openalex.org/W2510497028","https://openalex.org/W2516883896","https://openalex.org/W2542381826","https://openalex.org/W2581387731","https://openalex.org/W2588161033","https://openalex.org/W2600029986","https://openalex.org/W4235723617","https://openalex.org/W6604254268","https://openalex.org/W6719727587","https://openalex.org/W6735304689"],"related_works":["https://openalex.org/W2952813363","https://openalex.org/W4378678253","https://openalex.org/W2911497689","https://openalex.org/W4360783045","https://openalex.org/W2770149305","https://openalex.org/W2972076240","https://openalex.org/W3167930666","https://openalex.org/W3014952856","https://openalex.org/W2964843961","https://openalex.org/W3010730661"],"abstract_inverted_index":{"In":[0,41],"deep":[1],"learning,":[2],"data":[3],"augmentation":[4],"is":[5,102],"important":[6],"to":[7,14,175],"increase":[8],"the":[9,23,26,63,67,96,113,121,150,173,194],"amount":[10,114],"of":[11,25,62,77,115,131],"training":[12,39,107],"images":[13,130],"obtain":[15],"higher":[16,204],"classification":[17,69,146],"accuracies.":[18],"Most":[19],"data-augmentation":[20,48,200],"methods":[21],"adopt":[22],"use":[24],"following":[27],"techniques:":[28],"cropping,":[29],"mirroring,":[30],"color":[31],"casting,":[32],"scaling":[33],"and":[34,90,108,111,133,160,167],"rotation":[35],"for":[36,104],"creating":[37,105],"additional":[38],"images.":[40],"this":[42],"paper,":[43],"we":[44,123,152,171],"propose":[45],"a":[46,55,75,85,92,125,144,154,181,186],"novel":[47,126],"method":[49,73],"that":[50,193],"transforms":[51],"an":[52,118,138],"image":[53,57,65,89],"into":[54],"new":[56,106],"containing":[58],"multiple":[59],"rotated":[60,88],"copies":[61],"original":[64],"in":[66,80,95,117,143],"operational":[68],"stage.":[70],"The":[71,190],"proposed":[72,199],"creates":[74],"grid":[76],"n\u00d7n":[78],"cells,":[79],"which":[81],"each":[82],"cell":[83],"contains":[84],"different":[86],"randomly":[87],"introduces":[91],"natural":[93,134],"background":[94],"newly":[97],"created":[98,124],"image.":[99,119],"This":[100],"algorithm":[101],"used":[103,153],"testing":[109],"images,":[110,151],"enhances":[112],"information":[116],"For":[120],"experiments,":[122],"dataset":[127],"with":[128,180,197],"aerial":[129,140],"cows":[132],"scene":[135],"backgrounds":[136],"using":[137],"unmanned":[139],"vehicle,":[141],"resulting":[142],"binary":[145],"problem.":[147],"To":[148],"classify":[149],"convolutional":[155],"neural":[156],"network":[157],"(CNN)":[158],"architecture":[159],"compared":[161],"two":[162],"loss":[163,166],"functions":[164],"(Hinge":[165],"cross-entropy":[168],"loss).":[169],"Additionally,":[170],"compare":[172],"CNN":[174,196],"classical":[176],"feature-based":[177],"techniques":[178],"combined":[179],"k-nearest":[182],"neighbor":[183],"classifier":[184],"or":[185],"support":[187],"vector":[188],"machine.":[189],"results":[191],"show":[192],"pre-trained":[195],"our":[198],"technique":[201],"yields":[202],"significantly":[203],"accuracies":[205],"than":[206],"all":[207],"other":[208],"approaches.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":1}],"updated_date":"2026-04-06T07:47:59.780226","created_date":"2025-10-10T00:00:00"}
