1 citations · 1 across the 1 of their papers we have counts for
5 papers
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification
Alexander Rietzler, Sebastian Stabinger, Paul Opitz +1
Aspect-Target Sentiment Classification (ATSC) is a subtask of Aspect-Based Sentiment Analysis (ABSA), which has many applications e.g. in e-commerce, where data and insights from r…
Evaluating CNNs on the Gestalt Principle of Closure
Gregor Ehrensperger, Sebastian Stabinger, Antonio Rodríguez Sánchez
Deep convolutional neural networks (CNNs) are widely known for their outstanding performance in classification and regression tasks over high-dimensional data. This made them a pop…
Increasing the adversarial robustness and explainability of capsule networks with -capsules
David Peer, Sebastian Stabinger, Antonio Rodriguez-Sanchez
In this paper we introduce a new inductive bias for capsule networks and call networks that use this prior -capsule networks. Our inductive bias that is inspired by TE neurons o…
Guided Labeling using Convolutional Neural Networks
Sebastian Stabinger, Antonio Rodriguez-Sanchez
Over the last couple of years, deep learning and especially convolutional neural networks have become one of the work horses of computer vision. One limiting factor for the applica…
Evaluation of Deep Learning on an Abstract Image Classification Dataset
Sebastian Stabinger, Antonio Rodriguez-Sanchez
Convolutional Neural Networks have become state of the art methods for image classification over the last couple of years. By now they perform better than human subjects on many of…