Hadley A. Witt

Jan 11, 2024 | biorxiv.org | Hadley A. Witt |Dhananjay Bhaskar |Ryan Huang |Emily T. Winn-Nuñez

AbstractUnderstanding morphological variation is an important task in many areas of computational biology. Recent studies have focused on developing computational tools for the task of sub-image selection which aims at identifying structural features that best describe the variation between classes of shapes. A major part in assessing the utility of these approaches is to demonstrate their performance on both simulated and real datasets.