<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-8EJZ06VJ</identifier><date>2021</date><creator>Cengiz, Korhan</creator><creator>Luo, Jing</creator><creator>Zhang, Qiu-Ming</creator><relation>documents/doc/8/URN_NBN_SI_doc-8EJZ06VJ_001.pdf</relation><relation>documents/doc/8/URN_NBN_SI_doc-8EJZ06VJ_001.txt</relation><format format_type="volume">45</format><format format_type="issue">5</format><format format_type="type">article</format><format format_type="extent">str. 659-665</format><identifier identifier_type="ISSN">0350-5596</identifier><identifier identifier_type="ISSN">1854-3871</identifier><identifier identifier_type="COBISSID_HOST">75287811</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-8EJZ06VJ</identifier><language>eng</language><publisher>Slovensko društvo Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">diabetična rinopatija</subject><subject language_type_id="slv">nevronske mreže</subject><subject language_type_id="slv">računalništvo</subject><subject language_type_id="slv">strojno učenje</subject><subject language_type_id="slv">umetna inteligenca</subject><title>An optimized deep learning based technique for grading and extraction of diabetic retinopathy severities</title></Record>