{"id":"https://openalex.org/W7119993396","doi":"https://doi.org/10.1016/j.imavis.2026.105897","title":"Enhancing UAV small target detection: A balanced accuracy-efficiency algorithm with tiered feature focus","display_name":"Enhancing UAV small target detection: A balanced accuracy-efficiency algorithm with tiered feature focus","publication_year":2026,"publication_date":"2026-01-10","ids":{"openalex":"https://openalex.org/W7119993396","doi":"https://doi.org/10.1016/j.imavis.2026.105897"},"language":"en","primary_location":{"id":"doi:10.1016/j.imavis.2026.105897","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.imavis.2026.105897","pdf_url":null,"source":{"id":"https://openalex.org/S177430994","display_name":"Image and Vision Computing","issn_l":"0262-8856","issn":["0262-8856","1872-8138"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Image and Vision Computing","raw_type":"journal-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/A5100853727","display_name":"Hanwei Guo","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanwei Guo","raw_affiliation_strings":["Department of Computer, North China Electric Power University, Baoding 071003, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer, North China Electric Power University, Baoding 071003, China","institution_ids":["https://openalex.org/I153473198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122630492","display_name":"Shugang Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I153473198","display_name":"North China Electric Power University","ror":"https://ror.org/04qr5t414","country_code":"CN","type":"education","lineage":["https://openalex.org/I153473198"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shugang Liu","raw_affiliation_strings":["Department of Computer, North China Electric Power University, Baoding 071003, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer, North China Electric Power University, Baoding 071003, China","institution_ids":["https://openalex.org/I153473198"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5122630492"],"corresponding_institution_ids":["https://openalex.org/I153473198"],"apc_list":{"value":2270,"currency":"USD","value_usd":2270},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08507861,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"167","issue":null,"first_page":"105897","last_page":"105897"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.5716000199317932,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.5716000199317932,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.23720000684261322,"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"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.023099999874830246,"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/overhead","display_name":"Overhead (engineering)","score":0.6330999732017517},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6252999901771545},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6169999837875366},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.6085000038146973},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.578499972820282},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.52920001745224},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5178999900817871},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5121999979019165},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5115000009536743},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4828999936580658}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8166000247001648},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.6330999732017517},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6252999901771545},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6169999837875366},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.6085000038146973},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.578499972820282},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.52920001745224},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5178999900817871},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5121999979019165},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5115000009536743},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4876999855041504},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4828999936580658},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.454800009727478},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41749998927116394},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3720000088214874},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3700999915599823},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.361299991607666},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3206999897956848},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C2778915421","wikidata":"https://www.wikidata.org/wiki/Q3643177","display_name":"Performance improvement","level":2,"score":0.2937999963760376},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.29030001163482666},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.2727000117301941},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.2687999904155731},{"id":"https://openalex.org/C35639132","wikidata":"https://www.wikidata.org/wiki/Q7452468","display_name":"Sequence labeling","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.263700008392334}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.imavis.2026.105897","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.imavis.2026.105897","pdf_url":null,"source":{"id":"https://openalex.org/S177430994","display_name":"Image and Vision Computing","issn_l":"0262-8856","issn":["0262-8856","1872-8138"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Image and Vision Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W2531409750","https://openalex.org/W2896155169","https://openalex.org/W2963037989","https://openalex.org/W2963351448","https://openalex.org/W2970987838","https://openalex.org/W2985384565","https://openalex.org/W2988452521","https://openalex.org/W3035396860","https://openalex.org/W3035414587","https://openalex.org/W3160439413","https://openalex.org/W3205100603","https://openalex.org/W4206335490","https://openalex.org/W4312820606","https://openalex.org/W4313065862","https://openalex.org/W4320002812","https://openalex.org/W4321504865","https://openalex.org/W4366598917","https://openalex.org/W4386065441","https://openalex.org/W4386076325","https://openalex.org/W4388159379","https://openalex.org/W4388795404","https://openalex.org/W4390873988","https://openalex.org/W4395108819","https://openalex.org/W4400724641","https://openalex.org/W4401894250","https://openalex.org/W4402716285","https://openalex.org/W4402727675","https://openalex.org/W4402754006","https://openalex.org/W4409366138","https://openalex.org/W4409366328","https://openalex.org/W4412531447","https://openalex.org/W4413146088","https://openalex.org/W4413147024","https://openalex.org/W4413147183"],"related_works":[],"abstract_inverted_index":null,"counts_by_year":[],"updated_date":"2026-01-11T23:08:45.486102","created_date":"2026-01-10T00:00:00"}
