<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-HJYITLRN</identifier><date>2023</date><creator>Ullah, Zaka</creator><relation>documents/doc/H/URN_NBN_SI_doc-HJYITLRN_001.pdf</relation><relation>documents/doc/H/URN_NBN_SI_doc-HJYITLRN_001.txt</relation><format format_type="volume">47</format><format format_type="issue">6</format><format format_type="type">article</format><format format_type="extent">str. 165-172</format><identifier identifier_type="DOI">10.31449/inf.v47i6.4645</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID">207960835</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-HJYITLRN</identifier><language>eng</language><publisher publisher_location="Ljubljana">Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">medicinske slike</subject><subject language_type_id="slv">možganski tumorji</subject><subject language_type_id="slv">rak (medicina)</subject><subject language_type_id="slv">umetna inteligenca</subject><title>Enhancement of pre-trained deep learning models to improve brain tumor classification</title></Record>