Mask Estimation Module

Mask estimation modules are neural network components designed to predict masks that selectively extract or remove information from input data, improving performance in various tasks. Current research focuses on optimizing mask generation strategies, including curriculum learning approaches that adjust mask complexity during training and methods that leverage attention mechanisms or transformers to model contextual information within the data. These advancements are significantly impacting fields like medical image segmentation, clinical trial design, and speech enhancement by enabling more efficient data utilization and improved model accuracy.