151 citations · 247 across the 19 of their papers we have counts for
19 papers
ALGAN: Time Series Anomaly Detection with Adjusted-LSTM GAN
Md Abul Bashar, Richi Nayak
Anomaly detection in time series data, to identify points that deviate from normal behaviour, is a common problem in various domains such as manufacturing, medical imaging, and cyb…
Informed Machine Learning, Centrality, CNN, Relevant Document Detection, Repatriation of Indigenous Human Remains
Md Abul Bashar, Richi Nayak, Gareth Knapman +2
Among the pressing issues facing Australian and other First Nations peoples is the repatriation of the bodily remains of their ancestors, which are currently held in Western scient…
Unsupervised Visual Time-Series Representation Learning and Clustering
Gaurangi Anand, Richi Nayak
Time-series data is generated ubiquitously from Internet-of-Things (IoT) infrastructure, connected and wearable devices, remote sensing, autonomous driving research and, audio-vide…
Nonnegative Matrix Factorization to understand Spatio-Temporal Traffic Pattern Variations during COVID-19: A Case Study
Anandkumar Balasubramaniam, Thirunavukarasu Balasubramaniam, Rathinaraja Jeyaraj +2
Due to the rapid developments in Intelligent Transportation System (ITS) and increasing trend in the number of vehicles on road, abundant of road traffic data is generated and avai…
A Semi-automatic Data Extraction System for Heterogeneous Data Sources: A Case Study from Cotton Industry
Richi Nayak, Thirunavukarasu Balasubramaniam, Sangeetha Kutty +2
With the recent developments in digitisation, there are increasing number of documents available online. There are several information extraction tools that are available to extrac…
Investigation of Topic Modelling Methods for Understanding the Reports of the Mining Projects in Queensland
Yasuko Okamoto, Thirunavukarasu Balasubramaniam, Richi Nayak
In the mining industry, many reports are generated in the project management process. These past documents are a great resource of knowledge for future success. However, it would b…