This paper takes a fresh look at the image authentication problem and proposes an
alternative framework for personalized authentication based on the hash learning …

Positive and unlabeled learning (PU learning) is a kind of problem whose goal is learning a
two-classes classifier with little proportion of positive samples and numerous unlabeled …

Deep neural networks (DNNs) are often prone to learn the spurious correlations between
target classes and bias attributes, like gender and race, inherent in a major portion of …

Multi-view learning can improve classification performance by combining information
between different views. Due to the similarity in different views of the dataset, sometimes the …

Classification is the operation of dividing various data into multiple classes where they share
quantitative and qualitative similarities. Classification has many use cases in engineering …

In this paper, the object recognition module of a visual auxiliary system, InVision, called IR-
VP, is presented.(1) Deep multimodal neural network (DMNN) is presented to enhance …