<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-L4E2MWVG</identifier><date>2024</date><creator>Sahmoudi, Yahya</creator><relation>documents/doc/L/URN_NBN_SI_doc-L4E2MWVG_001.pdf</relation><relation>documents/doc/L/URN_NBN_SI_doc-L4E2MWVG_001.txt</relation><format format_type="issue">1</format><format format_type="volume">43</format><format format_type="type">article</format><format format_type="extent">str. 67-84</format><identifier identifier_type="DOI">105566/ias.3009</identifier><identifier identifier_type="ISSN">1580-3139</identifier><identifier identifier_type="COBISSID">245081091</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-L4E2MWVG</identifier><language>eng</language><publisher publisher_location="Ljubljana">Društvo za stereologijo in kvantitativno analizo slike, Medicinska fakulteta</publisher><source>Image analysis and stereology</source><rights>BY</rights><subject language_type_id="slv">Fourierjevi momenti</subject><subject language_type_id="slv">prepoznavanje vzorcev</subject><subject language_type_id="slv">rekonstrukcija slik</subject><subject language_type_id="slv">strojno učenje</subject><subject language_type_id="slv">umetna inteligenca</subject><subject language_type_id="slv">zaznavanje objektov</subject><title>Improving the machine learning performance for image recognition using a new set of mountain Fourier moments</title></Record>