Navigating in the latent space of StyleGAN has shown effectiveness for f...
Sparse-view computed tomography (CT) – using a small number of projectio...
Cross-corpus speech emotion recognition (SER) seeks to generalize the ab...
Online continual learning (CL) studies the problem of learning continuou...
While various deep learning methods have been proposed for low-dose comp...
Recent works for face editing usually manipulate the latent space of Sty...
Sparse-view computed tomography (CT) is a promising solution for expedit...
Since stroke is the main cause of various cerebrovascular diseases, deep...
Lung nodule malignancy prediction has been enhanced by advanced deep-lea...
Medical image segmentation is a challenging task with inherent ambiguity...
Low-dose computed tomography (CT) images suffer from noise and artifacts...
Noisy annotations such as missing annotations and location shifts often ...
Learning from noisy data is a challenging task that significantly degene...
This paper studies 3D low-dose computed tomography (CT) imaging. Althoug...
The goal of image ordinal estimation is to estimate the ordinal label of...
Speech emotion recognition (SER) plays a vital role in improving the
int...
As a unique biometric that can be perceived at a distance, gait has broa...
To minimize the impact of age variation on face recognition, age-invaria...
The presence of high-density objects such as metal implants and dental
f...
There are considerable interests in automatic stroke lesion segmentation...
Crowd Counting has important applications in public safety and pandemic
...
Since 2016, deep learning (DL) has advanced tomographic imaging with
rem...
Digital breast tomosynthesis (DBT) exams should utilize the lowest possi...
The performance of medical image classification has been enhanced by dee...
Existing deep clustering methods rely on contrastive learning for
repres...
Digital mammography is still the most common imaging tool for breast can...
LDCT has drawn major attention in the medical imaging field due to the
p...
Age progression and regression aim to synthesize photorealistic appearan...
Gait recognition plays a vital role in human identification since gait i...
Lowering the radiation dose in computed tomography (CT) can greatly redu...
To minimize the effects of age variation in face recognition, previous w...
Although impressive results have been achieved for age progression and
r...
The progression of lung cancer implies the intrinsic ordinal relationshi...
Deep learning-based methods have achieved promising performance in early...
Face aging is to render a given face to predict its future appearance, w...
The high risk population of cardiovascular disease (CVD) is simultaneous...
Ordinal regression is a type of regression techniques used for predictin...
Deep neural network based methods have achieved promising results for CT...
Cine cardiac magnetic resonance imaging (MRI) is widely used for diagnos...
Breast CT provides image volumes with isotropic resolution in high contr...
X-ray computed tomography (CT) is widely used in clinical practice. The
...
Face aging is of great importance for cross-age recognition and
entertai...
Positron emission tomography (PET) is widely used in clinical practice.
...
Cone-beam breast computed tomography (CT) provides true 3D breast images...
Magnetic resonance imaging (MRI) is widely used for screening, diagnosis...
Photoacoustic tomography seeks to reconstruct an acoustic initial pressu...
Magnetic resonance imaging (MRI) is a widely used medical imaging modali...
X-ray computed tomography (CT) reconstructs cross-sectional images from
...
Computer vision researchers prefer to estimate the age from face images ...
Recently, deep learning has transformed many fields including medical
im...