Integrating machine learning methods into a PdM system provides a promising solution for optimizing maintenance strategies, preventing equipment failures on the production line, and reducing downtime.

In this article, we propose an image coding for machines (ICMs) paradigm based on contrastive learning in a fully supervised manner to boost semantic segmentation of compressed RSIs.