Fine-grained Classification of Solder Joints with {\alpha}-skew Jensen-Shannon Divergence. (arXiv:2209.09857v1 [cs.CV])

Solder joint inspection (SJI) is a critical process in the production of
printed circuit boards (PCB). Detection of solder errors during SJI is quite
challenging as the solder joints have very small sizes and can take various
shapes. In this study, we first show that solders have low feature diversity,
and that the SJI can be carried out as a fine-grained image classification task
which focuses on hard-to-distinguish object classes. To improve the
fine-grained classification accuracy, penalizing confident model predictions …

alpha arxiv classification divergence fine-grained skew