Towards efficient melt pool tracking in Additive Manufacturing via semi-supervised Semantic Segmentation
Monitoring and characterizing melt pool dynamics in additive manufacturing is essential for understanding complex thermal and material behaviors that govern layer formation. Melt pool characteristics, such as size, shape, and dynamics, directly influence microstructure evolution, mechanical properties, and dimensional accuracy of the printed part. Therefore, accurate and efficient methods for melt
