Evaluating infrared thermographic imaging technology in the detection and quantification of tick burdens in cattle by Mudau, Fhulufhelo

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Development of scalable hybrid switching-based software-defined networking using reinforcement learning by Blose, Max

“…To ensure that the machine learning algorithm is able to discover a sufficient amount of possible routes and has a sufficient understanding of the network environment, sufficient training and evaluation episodes should be conducted. …”
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Development of scalable hybrid switching-based software-defined networking using reinforcement learning by Blose, Max

“…To ensure that the machine learning algorithm is able to discover a sufficient amount of possible routes and has a sufficient understanding of the network environment, sufficient training and evaluation episodes should be conducted. …”
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Integrated use of polarimetric Synthetic Aperture Radar (SAR) and optical image data for land cover mapping using an object-based approach by De Beyer, Leigh Helen

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Combinatorial evolution of feedforward neural network models for chemical processes by Schmitz, Gregor Peter Josef

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Quantifying phytoplankton biomass and sediment in river plumes along the Agulhas Bank using remotely sensed data with deep learning techniques by Pillay, Humeshni

“…For the developed [Chl-a] MLP algorithm, the constrained and full MLP models were similar, with C2RCC's AC producing the best results. …”
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Molecular dynamics simulations of the electrical conductivities of high temperature metallurgical slags by Mongalo, Lehlohonolo

“…Two layer MLP feedforward ANN models, using the resilient back propagation algorithm for training, were used to predict conductivities. …”
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Towards a framework for multi class statistical modelling of shape, intensity, and kinematics in medical images by Fouefack, Jean-Rassaire

“…Both sampling and parametric based registration algorithms are proposed, which allow the establishment of dense correspondence across volumetric shapes (such as tetrahedral meshes) while preserving the spatial relationship between them. …”
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Towards a framework for multi class statistical modelling of shape, intensity and kinematics in medical images by Fouefack, Jean-Rassaire

“…Both sampling and parametric based registration algorithms are proposed, which allow the establishment of dense correspondence across volumetric shapes (such as tetrahedral meshes) while preserving the spatial relationship between them. …”
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Adaptive digital image correlation using neural networks by Atkinson, Devan James

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Process monitoring and fault diagnosis using random forests by Auret, Lidia

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Detecting change in complex process systems with phase space methods by Botha, Paul Jacobus

“…The first method considered was a change-point algorithm that is based on singular spectrum analysis. …”
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A Comparison Between Machine Learning Techniques to Find Leaks in Pipe Networks

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Modeling cross-border financial flows using a network theoretic approach

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Tracking with context by Du Toit, Carlo

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Tree species identification and leaf segmentation from natural images using deep semi-supervised learning by Homan, Dewald

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Process monitoring with restricted Boltzmann machines by Moody, John Matali

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Personalized fall detection monitoring system based on user movements

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Classification and visualisation of text documents using networks by Phaweni, Thembani

“…We also applied three machine learning algorithms, naïve Bayes, neural networks and support vector machines. …”
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Implementation and evaluation of two prediction techniques for the Lorenz time series by Huddlestone, Grant E.

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