Abstract
This paper uses Deep Learning to classify if a display panel with defects in the manufacturing line can be repaired. Both tabular data and images are fused together to make predictions, with separate feature extraction undertaken for each of the modalities. The model's predictions achieve high Average Precision as well as robust Precision values in the high Recall regions, which makes it practical for deployment. We also demonstrate superior results with multi‐modal data compared to only tabular data.
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