Pengxin Luo

Abstract Analog gauges are fundamental for data acquisition in numerous industrial sectors, yet the automated reading of these devices is significantly hampered by a scarcity of large-scale, comprehensively annotated datasets. This data bottleneck impedes the development of robust and accurate computer vision algorithms. Here we introduce SyncG, a large-scale synthetic benchmark created to address this critical gap.