<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-PBSTSRCN</identifier><date>2025</date><creator>Shangguan, Tonghang</creator><creator>Yang, Cai</creator><creator>Zhang, Yingqi</creator><relation>documents/doc/P/URN_NBN_SI_doc-PBSTSRCN_001.pdf</relation><relation>documents/doc/P/URN_NBN_SI_doc-PBSTSRCN_001.txt</relation><format format_type="volume">49</format><format format_type="issue">6</format><format format_type="type">article</format><format format_type="extent">str. 147-158</format><identifier identifier_type="DOI">10.31449/inf.v49i6.7226</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">235695107</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-PBSTSRCN</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">model ICU-net</subject><subject language_type_id="slv">računalniška tomografija</subject><subject language_type_id="slv">sevanje</subject><subject language_type_id="slv">šum</subject><subject language_type_id="slv">umetna inteligenca</subject><title>ICU-net</title><title>a u-shaped low-dose CT image denoising network based on codec structure</title></Record>