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1 article(s) from Regev-Rudzki, Neta

The role of convolutional neural networks in scanning probe microscopy: a review

Ido Azuri,
Irit Rosenhek-Goldian,
Neta Regev-Rudzki,
Georg Fantner and
Sidney R. Cohen

Beilstein J. Nanotechnol. 2021, 12, 878–901, doi:10.3762/bjnano.12.66

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Figure 1: Linear decision boundary (green straight line) that separates between samples belonging to two diff...

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Figure 2: Performance as function of sample data set size for traditional machine learning algorithms and dee...

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Figure 3: Upper left: example of a deep neural network (DNN). Upper right: example of a shallow neural networ...

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Figure 4: (a) Description of the convolutional layer of a CNN and (b) the convolution operation. In (b) the o...

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Figure 5: Loss function as a function of the number of epochs for the training set (blue line) and the testin...

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Figure 6: Predictions of the probability for a healthy cytoskeleton made by the model on testing set and trea...

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Figure 7: Example of images of healthy (top) and diseased (bottom) Pf-EV exposed cells from the test set and ...

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Figure 8: Average intensity for all images in the testing set and the images of treated cytoskeleton for (a) ...

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Figure 9: Class activation maps shown below the AFM images for selected images of healthy and Pf-EV-exposed c...

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Figure 10: Class activation maps shown below the AFM images for selected images of healthy and Pf-EV-exposed c...

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Review

Published 13 Aug 2021

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