Membership function of output for tank 2. by Tamiru Demelash Kassie (20678515)

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... by G. Christopher Marais (21492084)

Modeling Molecularly Imprinted Nanoparticles with LNKD: A Resource Efficient Algorithm for Polymer Cross-Linking by Emma Stevens (22257358)

“…Here, we propose LNKD (Linking Nodes in KD-trees), a resource-efficient algorithm for predicting pairs of reactive atoms in pre-cross-linked 3D structures of monomers that applies not only to the modeling of MIPs, but also chemical cross-linking in other materials. …”

Membership function of error E1 for tank 1. by Tamiru Demelash Kassie (20678515)

Membership function of error E2 for tank 2. by Tamiru Demelash Kassie (20678515)

Variations of loss functions versus epoch number. by Xueliang Guo (4797057)

A comparison of the original images with the filtered images with the uniform window. by Abeer Aljohani (18497914)

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Confusion matrix values for different size of test samples and different choice of random states. by Abeer Aljohani (18497914)

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Comparison of the results obtained with the proposed method with other methods in literature. by Abeer Aljohani (18497914)

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A comparison of the spectral component of normal and abnormal images combined with the uniform window. by Abeer Aljohani (18497914)

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A visual representation of the windows used in the study. by Abeer Aljohani (18497914)

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The spectral component of normal peoples and Covid-19 infected peoples. by Abeer Aljohani (18497914)

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A comparison of the original images with the filtered images with the binomial window. by Abeer Aljohani (18497914)

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The effect of test set size and number of nodes on the values of confusion matrix using SVM combined with the uniform window. by Abeer Aljohani (18497914)

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Graphical illustration of a spectral approach for training support vector machine. by Abeer Aljohani (18497914)

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Accuracy of the support vector machines for different proportion of test samples and different length of nodes used for training. by Abeer Aljohani (18497914)

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Confusion matrix representation of classification outcomes. by Abeer Aljohani (18497914)

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The parametric study of the confusion matrix values for different proportion of test samples vs number of nodes from the spectral space. by Abeer Aljohani (18497914)

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ROC and precision plots of SVM showing the details of accuracy. by Abeer Aljohani (18497914)

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Classification Report of the SVM classifier without using any window. by Abeer Aljohani (18497914)

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