OpenAI has recently released GPT-4 (a.k.a. ChatGPT plus), which is
demon...
Data augmentation strategies are actively used when training deep neural...
It is important to quantify the uncertainty of input samples, especially...
Quantitative assessment of the abdominal region from clinically acquired...
The availability of large labeled datasets is the key component for the
...
Quantifying COVID-19 infection over time is an important task to manage ...
One principal approach for illuminating a black-box neural network is fe...
Consistent segmentation of COVID-19 patient's CT scans across multiple t...
Convolutional neural networks are showing promise in the automatic diagn...
Neural networks have demonstrated remarkable performance in classificati...
Is critical input information encoded in specific sparse pathways within...
Disentangled representations can be useful in many downstream tasks, hel...
Chest computed tomography (CT) has played an essential diagnostic role i...
In this paper we introduce OperA, a transformer-based model that accurat...
Medical imaging data suffers from the limited availability of annotation...
Segmentation of Multiple Sclerosis (MS) lesions in longitudinal brain MR...
Recent advances in deep learning have resulted in great successes in var...
Spine injections are commonly performed in several clinical procedures. ...
Attributing the output of a neural network to the contribution of given ...
The ambiguity of the decision-making process has been pointed out as the...
This paper deals with a method for generating realistic labeled masses.
...
In this study, a novel computer aided diagnosis (CADx) framework is devi...
Human face analysis is an important task in computer vision. According t...
In face-related applications with a public available dataset, synthesizi...
In convolutional neural networks (CNNs), the filter grouping in convolut...
With the recent substantial growth of media such as YouTube, a considera...