18 citations · 36 across the 7 of their papers we have counts for
9 papers
An operational framework to automatically evaluate the quality of weather observations from third-party stations
Quanxi Shao, Ming Li, Joel Janek Dabrowski +4
With increasing number of crowdsourced private automatic weather stations (called TPAWS) established to fill the gap of official network and obtain local weather information for va…
Smart Headset, Computer Vision and Machine Learning for Efficient Prawn Farm Management
Mingze Xi, Ashfaqur Rahman, Chuong Nguyen +2
Understanding the growth and distribution of the prawns is critical for optimising the feed and harvest strategies. An inadequate understanding of prawn growth can lead to reduced…
Deep Learning for Prawn Farming: Forecasting and Anomaly Detection
Joel Janek Dabrowski, Ashfaqur Rahman, Andrew Hellicar +2
We present a decision support system for managing water quality in prawn ponds. The system uses various sources of data and deep learning models in a novel way to provide 24-hour f…
HazeDose: Design and Analysis of a Personal Air Pollution Inhaled Dose Estimation System using Wearable Sensors
Ke Hu, Ashfaqur Rahman, Hassan Habibi Gharakheili +1
Nowadays air pollution becomes one of the biggest world issues in both developing and developed countries. Helping individuals understand their air pollution exposure and health ri…
Enforcing Mean Reversion in State Space Models for Prawn Pond Water Quality Forecasting
Joel Janek Dabrowski, Ashfaqur Rahman, Daniel Edward Pagendam +1
The contribution of this study is a novel approach to introduce mean reversion in multi-step-ahead forecasts of state-space models. This approach is demonstrated in a prawn pond wa…
Deep Learning and Statistical Models for Time-Critical Pedestrian Behaviour Prediction
Joel Janek Dabrowski, Johan Pieter de Villiers, Ashfaqur Rahman +1
The time it takes for a classifier to make an accurate prediction can be crucial in many behaviour recognition problems. For example, an autonomous vehicle should detect hazardous…