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11/05/2021
Disaster mapping from satellites: damage detection with crowdsourced point labels
High-resolution satellite imagery available immediately after disaster e...
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02/11/2021
Echo State Networks for Reinforcement Learning
Echo State Networks (ESNs) are a type of single-layer recurrent neural n...
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07/02/2020
Mining and Tailings Dam Detection In Satellite Imagery Using Deep Learning
This work explores the combination of free cloud computing, free open-so...
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11/29/2018
Uncertainty propagation in neural networks for sparse coding
A novel method to propagate uncertainty through the soft-thresholding no...
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11/29/2018
BCCNet: Bayesian classifier combination neural network
Machine learning research for developing countries can demonstrate clear...
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07/15/2018
Spatio-Temporal Structured Sparse Regression with Hierarchical Gaussian Process Priors
This paper introduces a new sparse spatio-temporal structured Gaussian p...
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07/09/2018
Ensemble Kalman Filtering for Online Gaussian Process Regression and Learning
Gaussian process regression is a machine learning approach which has bee...
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04/27/2017
Compressive Sensing Approaches for Autonomous Object Detection in Video Sequences
Video analytics requires operating with large amounts of data. Compressi...
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04/27/2017
Structured Sparse Modelling with Hierarchical GP
In this paper a new Bayesian model for sparse linear regression with a s...
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11/02/2016
Learning Methods for Dynamic Topic Modeling in Automated Behaviour Analysis
Semi-supervised and unsupervised systems provide operators with invaluab...
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06/27/2016
Dynamic Hierarchical Dirichlet Process for Abnormal Behaviour Detection in Video
This paper proposes a novel dynamic Hierarchical Dirichlet Process topic...
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06/27/2016