… of new and powerful deep learning (DL) techniques, which … – may hamper the effectiveness
of classifiers. In order to solve … of the most widely used classifiers in the literature. For each …

… However, the application of deep learning techniques to … of pre-trained deep learning
classifiers; namely COVIDX-Net … metric for the results of our deep learning classifiers, as given in …

… with deep learning models for text classification. We present a novel framework, DeepWordBug
to generate adversarial text sequences that can mislead deep learning … deep learning …

… If we use the deep learning classifier that is built by the adversary, the classification errors
are shown in Table III. These classification errors are combinations of the error of the original …

… based classifier and a deep learningbased classifier to … learning (CNN) classifier. Our results
demonstrate the power of ensembling feature-based and representation learning classifiers …

… Although conventional machine learning algorithms that … , AI classifiers using conventional
machine learning algorithms … these issues, deep learning-based CNN classifiers, which …

… Deep learning is a new area of machine learning research. … to use Deep learning from open
source H2O machine learning … compare Deep learning method from H20 machine learning …

… Deep learning being a latest technology playing a vital role in helping human in many aspects.
A thorough review of the research papers on the various classifiers … new deep learning …

… A two-class linear classifier computes a weighted sum of the … Since the 1960s we have known
that linear classifiers can only … A linear classifier, or any other 'shallow' classifier operating …

… Deep learning techniques can revolutionize modern medicine … classifier which is cascaded
with the SAE performs the classification based on these learned features. Different classifiers …