Event Details
Deep and Light Capsule Network (DL-CapsNet)
Presenter: Amirali Baniasadi
Supervisor:
Date: Fri, July 15, 2022
Time: 11:00:00 - 00:00:00
Place: ZOOM - Please see below.
ABSTRACT
Zoom link: https://uvic.zoom.us/j/81672827284
Meeting ID: 816 7282 7284
Abstract:
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 than CNNs in detecting images with overlapping categories and those with applied affine transformations. In this work, we propose a deep variant of CapsNet consisting of several capsule layers. In addition, we design the Capsule Summarization layer to reduce the complexity by reducing the number of parameters. DL-CapsNet, while being highly accurate, employs a small number of parameters and delivers faster training and inference. DL-CapsNet can process complex datasets with a high number of categories.