<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:doc-RD89QR71</identifier><date>2021</date><creator>Gams, Matjaž</creator><creator>Gjoreski, Hristijan</creator><creator>Gjoreski, Martin</creator><creator>Kalabakov, Stefan</creator><relation>documents/doc/R/URN_NBN_SI_doc-RD89QR71_001.pdf</relation><relation>documents/doc/R/URN_NBN_SI_doc-RD89QR71_001.txt</relation><format format_type="issue">2</format><format format_type="volume">45</format><format format_type="type">article</format><format format_type="extent">str. 289-296</format><identifier identifier_type="ISSN">0350-5596</identifier><identifier identifier_type="COBISSID">104064771</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-RD89QR71</identifier><language>eng</language><publisher>Slovensko društvo Informatika</publisher><source>Informatica (Ljubljana)</source><rights>BY</rights><subject language_type_id="slv">globoko učenje</subject><subject language_type_id="slv">preneseno učenje</subject><subject language_type_id="slv">strojno učenje</subject><title>Analysis of deep transfer learning using deedConvLSTM for human activity recognition from wearable sensors</title></Record>