69 citations · 112 across the 6 of their papers we have counts for
3 papers · 1 filter
Comparative Analysis of Segment Anything Model and U-Net for Breast Tumor Detection in Ultrasound and Mammography Images
Mohsen Ahmadi, Masoumeh Farhadi Nia, Sara Asgarian +4
In this study, the main objective is to develop an algorithm capable of identifying and delineating tumor regions in breast ultrasound (BUS) and mammographic images. The technique…
Supervised Multi-Regional Segmentation Machine Learning Architecture for Digital Twin Applications in Coastal Regions
Mohsen Ahmadi, Ahmad Gholizadeh Lonbar, Mohammadsadegh Nouri +4
This study explores the use of a digital twin model and deep learning method to build a global terrain and altitude map based on USGS information. The goal is to artistically repre…
Application of Segment Anything Model for Civil Infrastructure Defect Assessment
Mohsen Ahmadi, Ahmad Gholizadeh Lonbar, Hajar Kazemi Naeini +4
This research assesses the performance of two deep learning models, SAM and U-Net, for detecting cracks in concrete structures. The results indicate that each model has its own str…