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A comparative study on feature selection for a risk prediction model for colorectal cancer
Methods This work is focused on colorectal cancer, assessing several feature ranking algorithms in terms of performance for a set of risk prediction models (Neural Networks, Support Vector Machines (SVM), Logistic Regression, k-Nearest Neighbors and Boosted Trees).
Combining shape and contour features to improve tool wear monitoring in milling processes
In this paper, a new system based on combinations of a shape descriptor and a contour descriptor has been proposed for classifying inserts in milling processes according to their wear level following a computer vision based approach.
Tool wear monitoring using an online, automatic and low cost system based on local texture
The best patch division configuration and texture descriptor for the WP achieves an accuracy of 90. 26% in the detection of the disposable cutting edges.
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