7 papers
PrunedCaps: A Case For Primary Capsules Discrimination
Ramin Sharifi, Pouya Shiri, Amirali Baniasadi
Capsule Networks (CapsNets) are a generation of image classifiers with proven advantages over Convolutional Neural Networks (CNNs). Better robustness to affine transformation and o…
DL-CapsNet: A Deep and Light Capsule Network
Pouya Shiri, Amirali Baniasadi
Capsule Network (CapsNet) is among the promising classifiers and a possible successor of the classifiers built based on Convolutional Neural Network (CNN). CapsNet is more accurate…
LE-CapsNet: A Light and Enhanced Capsule Network
Pouya Shiri, Amirali Baniasadi
Capsule Network (CapsNet) classifier has several advantages over CNNs, including better detection of images containing overlapping categories and higher accuracy on transformed ima…
Convolutional Fully-Connected Capsule Network (CFC-CapsNet): A Novel and Fast Capsule Network
Pouya Shiri, Amirali Baniasadi
A Capsule Network (CapsNet) is a relatively new classifier and one of the possible successors of Convolutional Neural Networks (CNNs). CapsNet maintains the spatial hierarchies bet…
Quick-CapsNet (QCN): A fast alternative to Capsule Networks
Pouya Shiri, Ramin Sharifi, Amirali Baniasadi
The basic computational unit in Capsule Network (CapsNet) is a capsule (vs. neurons in Convolutional Neural Networks (CNNs)). A capsule is a set of neurons, which form a vector. Ca…
Generating Synthetic Contrast-Enhanced Chest CT Images from Non-Contrast Scans Using Slice-Consistent Brownian Bridge Diffusion Network
Pouya Shiri, Xin Yi, Neel P. Mistry +5
Contrast-enhanced computed tomography (CT) imaging is essential for diagnosing and monitoring thoracic diseases, including aortic pathologies. However, contrast agents pose risks s…