<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-357Z9W2C</identifier><date>2024</date><creator>Martins da Cruz, Jose-Marcio</creator><relation>documents/doc/3/URN_NBN_SI_doc-357Z9W2C_001.pdf</relation><relation>documents/doc/3/URN_NBN_SI_doc-357Z9W2C_001.txt</relation><format format_type="issue">2</format><format format_type="volume">43</format><format format_type="type">article</format><format format_type="extent">str. 121-130</format><identifier identifier_type="ISSN">1580-3139</identifier><identifier identifier_type="COBISSID">245133059</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-357Z9W2C</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">entropija</subject><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">ocena kakovosti segmentacije</subject><subject language_type_id="slv">segmentacija slik</subject><subject language_type_id="slv">umetna inteligenca</subject><title>A posteriori deep learning segmentation quality estimation based on prediction entropy</title></Record>