80 citations · 97 across the 9 of their papers we have counts for
9 papers
A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets
Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel +1
Health mention classification deals with the disease detection in a given text containing disease words. However, non-health and figurative use of disease words adds challenges to…
Improving Health Mentioning Classification of Tweets using Contrastive Adversarial Training
Pervaiz Iqbal Khan, Shoaib Ahmed Siddiqui, Imran Razzak +2
Health mentioning classification (HMC) classifies an input text as health mention or not. Figurative and non-health mention of disease words makes the classification task challengi…
Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak +4
A Machine-Critical Application is a system that is fundamentally necessary to the success of specific and sensitive operations such as search and recovery, rescue, military, and em…
Distributed Optimization of Graph Convolutional Network using Subgraph Variance
Taige Zhao, Xiangyu Song, Jianxin Li +2
In recent years, Graph Convolutional Networks (GCNs) have achieved great success in learning from graph-structured data. With the growing tendency of graph nodes and edges, GCN tra…
Understanding Information Spreading Mechanisms During COVID-19 Pandemic by Analyzing the Impact of Tweet Text and User Features for Retweet Prediction
Pervaiz Iqbal Khan, Imran Razzak, Andreas Dengel +1
COVID-19 has affected the world economy and the daily life routine of almost everyone. It has been a hot topic on social media platforms such as Twitter, Facebook, etc. These socia…
DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media
Hamad Zogan, Imran Razzak, Shoaib Jameel +1
Twitter is currently a popular online social media platform which allows users to share their user-generated content. This publicly-generated user data is also crucial to healthcar…