One of the persistent topics in digital forensic research in recent years has been the problem of finding all things similar. Developed tools usually take on the form of similarit...
Background: Overfitting the data is a salient issue for classifier design in small-sample settings. This is why selecting a classifier from a constrained family of classifiers, on...
Jianping Hua, James Lowey, Zixiang Xiong, Edward R...
We present a novel method for feature matching across widely separated color images. The proposed approach is robust and can support various correspondence based algorithms e.g. t...
In manipulating data such as in supervised learning, we often extract new features from original features for the purpose of reducing the dimensions of feature space and achieving ...
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...
Su-In Lee, Vassil Chatalbashev, David Vickrey, Dap...