most citedRadial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability

41 citations · 70 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20241 cited

Deep Learning for Robust and Explainable Models in Computer Vision

Mohammadreza Amirian

Recent breakthroughs in machine and deep learning (ML and DL) research have provided excellent tools for leveraging enormous amounts of data and optimizing huge models with million…

cs.CV202427 cited

Artifact Reduction in 3D and 4D Cone-beam Computed Tomography Images with Deep Learning -- A Review

Mohammadreza Amirian, Daniel Barco, Ivo Herzig +1

Deep learning based approaches have been used to improve image quality in cone-beam computed tomography (CBCT), a medical imaging technique often used in applications such as image…

cs.CV2022

Trace and Detect Adversarial Attacks on CNNs using Feature Response Maps

Mohammadreza Amirian, Friedhelm Schwenker, Thilo Stadelmann

The existence of adversarial attacks on convolutional neural networks (CNN) questions the fitness of such models for serious applications. The attacks manipulate an input image suc…

cs.CV202241 cited

Radial Basis Function Networks for Convolutional Neural Networks to Learn Similarity Distance Metric and Improve Interpretability

Mohammadreza Amirian, Friedhelm Schwenker

Radial basis function neural networks (RBFs) are prime candidates for pattern classification and regression and have been used extensively in classical machine learning application…

eess.IV20221 cited

PrepNet: A Convolutional Auto-Encoder to Homogenize CT Scans for Cross-Dataset Medical Image Analysis

Mohammadreza Amirian, Javier A. Montoya-Zegarra, Jonathan Gruss +5

With the spread of COVID-19 over the world, the need arose for fast and precise automatic triage mechanisms to decelerate the spread of the disease by reducing human efforts e.g. f…