{"id":"https://openalex.org/W4392025211","doi":"https://doi.org/10.1109/aipr60534.2023.10440706","title":"Applications of Deep Learning Neural Networks for Classifying Mesoamerican Historical Art Objects and Documents","display_name":"Applications of Deep Learning Neural Networks for Classifying Mesoamerican Historical Art Objects and Documents","publication_year":2023,"publication_date":"2023-09-27","ids":{"openalex":"https://openalex.org/W4392025211","doi":"https://doi.org/10.1109/aipr60534.2023.10440706"},"language":"en","primary_location":{"id":"doi:10.1109/aipr60534.2023.10440706","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aipr60534.2023.10440706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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/A5023672303","display_name":"Andrew Kalukin","orcid":"https://orcid.org/0000-0001-5644-7096"},"institutions":[{"id":"https://openalex.org/I4210155636","display_name":"Remote Sensing Solutions (United States)","ror":"https://ror.org/04tbz4c44","country_code":"US","type":"company","lineage":["https://openalex.org/I4210155636"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew Kalukin","raw_affiliation_strings":["Through Sensing, LLC,Arlington,VA","Through Sensing, LLC, Arlington, VA"],"affiliations":[{"raw_affiliation_string":"Through Sensing, LLC,Arlington,VA","institution_ids":["https://openalex.org/I4210155636"]},{"raw_affiliation_string":"Through Sensing, LLC, Arlington, VA","institution_ids":["https://openalex.org/I4210155636"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5023672303"],"corresponding_institution_ids":["https://openalex.org/I4210155636"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34066793,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"01","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12981","display_name":"Conservation Techniques and Studies","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1206","display_name":"Conservation"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12981","display_name":"Conservation Techniques and Studies","score":0.9876999855041504,"subfield":{"id":"https://openalex.org/subfields/1206","display_name":"Conservation"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.986299991607666,"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/T11212","display_name":"Cultural Heritage Materials Analysis","score":0.9726999998092651,"subfield":{"id":"https://openalex.org/subfields/1204","display_name":"Archeology"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7287158966064453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5982940793037415},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5685828328132629},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.566838264465332},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4239964485168457},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3668324947357178}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7287158966064453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5982940793037415},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5685828328132629},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.566838264465332},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4239964485168457},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3668324947357178}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr60534.2023.10440706","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/aipr60534.2023.10440706","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310017","display_name":"University of Connecticut","ror":"https://ror.org/02der9h97"},{"id":"https://openalex.org/F4320310173","display_name":"University of Massachusetts","ror":"https://ror.org/0072zz521"},{"id":"https://openalex.org/F4320312726","display_name":"University of Oregon","ror":"https://ror.org/0293rh119"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W2063012630","https://openalex.org/W2133664003","https://openalex.org/W2323426358","https://openalex.org/W2325300293","https://openalex.org/W3004490985","https://openalex.org/W3107809843","https://openalex.org/W3143866280","https://openalex.org/W6773487996"],"related_works":["https://openalex.org/W2731899572","https://openalex.org/W3215138031","https://openalex.org/W4321369474","https://openalex.org/W3009238340","https://openalex.org/W4360585206","https://openalex.org/W4285208911","https://openalex.org/W3082895349","https://openalex.org/W4213079790","https://openalex.org/W2248239756","https://openalex.org/W4323565446"],"abstract_inverted_index":{"Deep":[0],"learning":[1,20],"neural":[2],"networks":[3],"were":[4],"applied":[5],"to":[6,15,48,55,62,106,112],"image":[7,64],"data":[8,47,50,75],"derived":[9],"from":[10,25,53,95],"digitized":[11],"Mesoamerican":[12,31],"historical":[13],"manuscripts":[14],"determine":[16],"whether":[17],"the":[18,43,73,93,101,110],"deep":[19],"system":[21,94],"can":[22],"differentiate":[23],"fragments":[24],"separate":[26],"samples":[27],"representing":[28],"several":[29],"different":[30],"cultures.":[32],"The":[33,66],"experiment":[34],"consisted":[35],"of":[36,42,45,57,60,68,87,103],"measuring":[37],"accuracy":[38,86,111],"as":[39],"a":[40],"function":[41],"ratio":[44,76,102],"testing":[46],"training":[49,74,104],"quantities,":[51],"ranging":[52],"0.3125%":[54],"80%":[56,107],"datasets":[58],"consisting":[59],"625":[61],"765":[63],"samples.":[65],"point":[67],"diminishing":[69],"returns":[70],"in":[71,84],"increasing":[72,100],"was":[77],"about":[78],"1%":[79],"(around":[80],"33":[81],"images),":[82],"resulting":[83],"an":[85],"87%.":[88],"Using":[89],"fewer":[90],"images":[91,105],"prevented":[92],"making":[96],"any":[97],"classification":[98],"distinctions;":[99],"gradually":[108],"increased":[109],"99%":[113],"asymptotically.":[114]},"counts_by_year":[],"updated_date":"2025-12-25T23:11:45.687758","created_date":"2025-10-10T00:00:00"}