31 citations · 100 across the 12 of their papers we have counts for
13 papers
Fruit Picker Activity Recognition with Wearable Sensors and Machine Learning
Joel Janek Dabrowski, Ashfaqur Rahman
In this paper we present a novel application of detecting fruit picker activities based on time series data generated from wearable sensors. During harvesting, fruit pickers pick f…
A Semi-supervised Approach for Activity Recognition from Indoor Trajectory Data
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. Machine learning allows to stu…
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…
Quality Control in Weather Monitoring with Dynamic Linear Models
Joel Janek Dabrowski, Ashfaqur Rahman, Ming Li +4
Decisions in agriculture are frequently based on weather. With an increase in the availability and affordability of off-the-shelf weather stations, farmers able to acquire localise…
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…
Sequence-to-Sequence Imputation of Missing Sensor Data
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 re…
ForecastNet: A Time-Variant Deep Feed-Forward Neural Network Architecture for Multi-Step-Ahead Time-Series Forecasting
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. These networks use parameter sharing by…
Channel Transition Invariant Fast Broadcasting Scheme
Mohammad Saidur Rahman, Ashfaqur Rahman
Fast broadcasting (FB) is a popular near video-on-demand system where a video is divided into equal size segments those are repeatedly transmitted over a number of channels followi…
Efficient Orthogonal Parametrisation of Recurrent Neural Networks Using Householder Reflections
Zakaria Mhammedi, Andrew Hellicar, Ashfaqur Rahman +1
The problem of learning long-term dependencies in sequences using Recurrent Neural Networks (RNNs) is still a major challenge. Recent methods have been suggested to solve this prob…