Over the past decade, deep learning has had a revolutionary impact on a broad range of
fields such as computer vision and image processing, computational photography, medical …

Background Computed tomography angiography (CTA) is very popular because it is
characterized by rapidity and accessibility. However, CTA is inferior to digital subtraction …

The study of nicotine addiction mechanism is of great significance in both nicotine
withdrawal and brain science. The detection of addiction-related brain connectivity using …

For diseases with high morbidity rates such as Glioblastoma Multiforme, the prognostic and
treatment planning pipeline requires a comprehensive analysis of imaging, clinical, and …

Out-of-distribution detection is one of the most critical issue in the deployment of machine
learning. The data analyst must assure that data in operation should be compliant with the …

Out-of-distribution detection has become an important theme in machine learning (ML) field,
since the recognition of unseen data either “similar” or not (in-or out-of-distribution) to the …

Generative models (eg, variational autoencoders, flow-based generative models, GANs)
usually involve finding a mapping from a known distribution, eg Gaussian, to an estimate of …

Data augmentation represents an opportunity for Artificial Intelligence applications, as it
aims at creating new synthetic data based on an existing baseline. In this paper, we present …