1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CV2022
DeepAngle: Fast calculation of contact angles in tomography images using deep learning
Arash Rabbani, Chenhao Sun, Masoud Babaei +3
DeepAngle is a machine learning-based method to determine the contact angles of different phases in the tomography images of porous materials. Measurement of angles in 3--D needs t…
eess.IV2022★ 1 cited
Automated segmentation and morphological characterization of placental histology images based on a single labeled image
Arash Rabbani, Masoud Babaei, Masoumeh Gharib
In this study, a novel method of data augmentation has been presented for the segmentation of placental histological images when the labeled data are scarce. This method generates…
cond-mat.mtrl-sci2020
DeePore: a deep learning workflow for rapid and comprehensive characterization of porous materials
Arash Rabbani, Masoud Babaei, Reza Shams +2
DeePore is a deep learning workflow for rapid estimation of a wide range of porous material properties based on the binarized micro-tomography images. By combining naturally occurr…