<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-0RDK3R9M</identifier><date>2024</date><creator>Dong, Shujan</creator><creator>Wang, Zhongwei</creator><relation>documents/doc/0/URN_NBN_SI_doc-0RDK3R9M_001.pdf</relation><relation>documents/doc/0/URN_NBN_SI_doc-0RDK3R9M_001.txt</relation><format format_type="issue">10</format><format format_type="volume">48</format><format format_type="type">article</format><format format_type="extent">str. 19-33</format><identifier identifier_type="DOI">10.31449/inf.v48i10.5919</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">216882435</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-0RDK3R9M</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">drža</subject><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">korekcije</subject><subject language_type_id="slv">media pipe blaze pose</subject><subject language_type_id="slv">MPP-YOLOv3</subject><subject language_type_id="slv">prepoznavanje</subject><subject language_type_id="slv">umetna inteligenca</subject><title>The application of action recognition based on MPP-YOLOv3 algorithm in posture correction</title></Record>