<?xml version="1.0" encoding="UTF-8"?><rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcq="http://purl.org/dc/terms/"><records count="1" morepages="false" start="1" end="1"><record rownumber="1"><dc:product_type>Journal Article</dc:product_type><dc:title>Confidence-Aware Photometric Stereo Networks Enabling End-to-End Normal and Depth Estimation for Smart Metrology</dc:title><dc:creator>Zhang, Yahui; Yang, Ru; Guo, Ping</dc:creator><dc:corporate_author/><dc:editor/><dc:description/><dc:publisher>IEEE</dc:publisher><dc:date>2025-04-01</dc:date><dc:nsf_par_id>10632381</dc:nsf_par_id><dc:journal_name>IEEE/ASME Transactions on Mechatronics</dc:journal_name><dc:journal_volume>30</dc:journal_volume><dc:journal_issue>2</dc:journal_issue><dc:page_range_or_elocation>910 to 920</dc:page_range_or_elocation><dc:issn>1083-4435</dc:issn><dc:isbn/><dc:doi>https://doi.org/10.1109/TMECH.2024.3481196</dc:doi><dcq:identifierAwardId>2229170; 2328032</dcq:identifierAwardId><dc:subject/><dc:version_number/><dc:location/><dc:rights/><dc:institution/><dc:sponsoring_org>National Science Foundation</dc:sponsoring_org></record></records></rdf:RDF>