We show how feature maps in convolutional networks are susceptible to spatial bias. Due to
a combination of architectural choices, the activation at certain locations is systematically …

Advances in representation learning have led to great success in understanding and
generating data in various domains. However, in modeling vector graphics data, the pure …

Although most fingerprint matching methods utilize minutia points and/or texture of
fingerprint images as fingerprint features, the frequency spectrum is also a useful feature …

Images can convey intense affective experiences and affect people on an affective level.
With the prevalence of online pictures and videos, evaluating emotions from visual content …

Diabetic retinopathy (DR) is a common fundus disease that leads to irreversible blindness,
which plagues the working-age population. Automatic medical imaging diagnosis provides a …

A modern deep neural network (DNN) for image classification tasks typically consists of two
parts: a backbone for feature extraction, and a head for feature encoding and class …

Automatic surveillance of early neoplasia in Barrett's esophagus (BE) is of great significance
for improving the survival rate of esophageal cancer. It remains, however, a challenging task …

Finding the correct category of wear particles is important to understand the tribological
behavior. However, manual identification is tedious and time-consuming. We here propose …

Recommender systems represent a critical field of AI technology applications. The core
function of a recommender system is to recommend items of interest to users, but if it is only …

Abstract Deep networks based Facial Expression Recognition (FER) have shown excellent
performance. Due to high computational cost and memory resources, it is hard to develop …