Introduction: Recently, the integration of deep learning techniques and computational materials science has catalyzed significant advances in the microstructural analysis of materials, particularly ...

Abstract: Once deployed, medical image analysis methods are often faced with unexpected image corruptions and noise perturbations. These unknown covariate shifts present significant challenges to deep ...

As shown below, the inferred masks predicted by our segmentation model trained on the dataset appear similar to the ground truth masks, but they lack precision in certain areas. Concrete structures ...

Abstract: Fine-grained flower image classification (FGFIC) is challenging due to high similarities among species and variations within species, especially with limited training data. Existing genetic ...