Machine Learning (ML) techniques have recently been applied to automate the wafer map pattern recognition problem. However, as manually annotating wafer map data is expensive and time-consuming, most of the research work leverage on public available dataset such as WM-811K with known probe technology agnostic labels. Probe technology specific wafer map patterns, especially multisite probe touchdown related patterns, have not been considered, as they are affected by specific wafer test methodology and require customized labeled data which are not readily available. In this paper, we propose a synthetic data augmented training method to enable automated wafer map recognition for multisite probe specific patterns.