no code implementations • 20 Apr 2023 • Joel Janek Dabrowski, Ashfaqur Rahman
For farmers and managers, the knowledge of when a picker bag is emptied is important for managing harvesting bins more effectively to minimise the time the picked fruit is left out in the heat (resulting in reduced shelf life).
no code implementations • 9 Jan 2023 • Mashud Rana, Ashfaqur Rahman, Daniel Smith
The increasingly wide usage of location aware sensors has made it possible to collect large volume of trajectory data in diverse application domains.
no code implementations • 5 Dec 2022 • Quanxi Shao, Ming Li, Joel Janek Dabrowski, Shuvo Bakar, Ashfaqur Rahman, Andrea Powell, Brent Henderson
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 various purposes, the data quality is a major concern in promoting their usage.
no code implementations • 14 Oct 2022 • Mingze Xi, Ashfaqur Rahman, Chuong Nguyen, Stuart Arnold, John McCulloch
Understanding the growth and distribution of the prawns is critical for optimising the feed and harvest strategies.
no code implementations • 4 Oct 2022 • Peter Baumgartner, Daniel Smith, Mashud Rana, Reena Kapoor, Elena Tartaglia, Andreas Schutt, Ashfaqur Rahman, John Taylor, Simon Dunstall
From an application perspective, we review applications of these methods to movement analytics in a general sense and across various industries.
no code implementations • 12 May 2022 • Joel Janek Dabrowski, Ashfaqur Rahman, Andrew Hellicar, Mashud Rana, Stuart Arnold
We present a decision support system for managing water quality in prawn ponds.
no code implementations • 26 Feb 2020 • Joel Janek Dabrowski, Johan Pieter de Villiers, Ashfaqur Rahman, Conrad Beyers
We show that, though the neural network model achieves an accuracy of 80%, it requires long sequences to achieve this (100 samples or more).
no code implementations • 25 Feb 2020 • Joel Janek Dabrowski, Ashfaqur Rahman
Although the sequence-to-sequence (encoder-decoder) model is considered the state-of-the-art in deep learning sequence models, there is little research into using this model for recovering missing sensor data.
1 code implementation • 11 Feb 2020 • Joel Janek Dabrowski, Yifan Zhang, Ashfaqur Rahman
Recurrent and convolutional neural networks are the most common architectures used for time series forecasting in deep learning literature.
1 code implementation • ICML 2017 • Zakaria Mhammedi, Andrew Hellicar, Ashfaqur Rahman, James Bailey
Our contributions are as follows; we first show that constraining the transition matrix to be unitary is a special case of an orthogonal constraint.