<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-VB7ATT1Q</identifier><date>2025</date><creator>Li, Wenyuan</creator><creator>Yang, Yuxuan</creator><relation>documents/doc/V/URN_NBN_SI_doc-VB7ATT1Q_001.pdf</relation><relation>documents/doc/V/URN_NBN_SI_doc-VB7ATT1Q_001.txt</relation><format format_type="issue">10</format><format format_type="volume">49</format><format format_type="type">article</format><format format_type="extent">str. 43-53</format><identifier identifier_type="DOI">10.31449/inf.v49i10.7148</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">239295747</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-VB7ATT1Q</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">kakovost slik</subject><subject language_type_id="slv">referenčna slika</subject><subject language_type_id="slv">umetna inteligenca</subject><subject language_type_id="slv">večnivojska fuzija</subject><subject language_type_id="eng">Vision Transformer</subject><title>Deep learning-based non-reference image quality assessment using vision transformer with multiscale dual branch fusion</title></Record>