66 citations · 137 across the 16 of their papers we have counts for
5 papers · 1 filter
Uncertainty Quantification in Multivariable Regression for Material Property Prediction with Bayesian Neural Networks
Longze Li, Jiang Chang, Aleksandar Vakanski +3
With the increased use of data-driven approaches and machine learning-based methods in material science, the importance of reliable uncertainty quantification (UQ) of the predicted…
Review of Machine Learning Methods for Additive Manufacturing of Functionally Graded Materials
Mohammad Karimzadeh, Deekshith Basvoju, Aleksandar Vakanski +3
Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-be-layer from 3D modeling data. Among AM applications, t…
Post-Hoc Explainability of BI-RADS Descriptors in a Multi-task Framework for Breast Cancer Detection and Segmentation
Mohammad Karimzadeh, Aleksandar Vakanski, Min Xian +1
Despite recent medical advancements, breast cancer remains one of the most prevalent and deadly diseases among women. Although machine learning-based Computer-Aided Diagnosis (CAD)…
Breast Ultrasound Tumor Classification Using a Hybrid Multitask CNN-Transformer Network
Bryar Shareef, Min Xian, Aleksandar Vakanski +1
Capturing global contextual information plays a critical role in breast ultrasound (BUS) image classification. Although convolutional neural networks (CNNs) have demonstrated relia…
Enhanced Sharp-GAN For Histopathology Image Synthesis
Sujata Butte, Haotian Wang, Aleksandar Vakanski +1
Histopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to pro…