Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Low-light images challenge both human perceptions and computer vision algorithms. It is
crucial to make algorithms robust to enlighten low-light images for computational …

Recent years have witnessed the growing interest in disease severity grading, especially for
ocular diseases based on fundus images. The existing grading methods are usually trained …

Existing methods on facial expression recognition (FER) are mainly trained in the setting
when all expression classes are fixed in advance. However, in real applications, expression …

The openness of application scenarios and the difficulties of data collection make it
impossible to prepare all kinds of expressions for training. Hence, detecting expression …

Deep learning has achieved good success in cardiac magnetic resonance imaging (MRI)
reconstruction, in which convolutional neural networks (CNNs) learn a mapping from the …

Magnetic resonance imaging (MRI) reconstruction is an active inverse problem which can
be addressed by conventional compressed sensing (CS) MRI algorithms that exploit the …

Compressed sensing magnetic resonance imaging (CS-MRI) is a technique aimed at
accelerating the data acquisition of MRI. While down-sampling in k-space proportionally …

Compressed sensing magnetic resonance imaging (CS-MRI) seeks to recover visual
information from subsampled measurements for diagnostic tasks. Traditional CS-MRI …

Convolutional neural network (CNN) has achieved great success in the compressed
sensing-based magnetic resonance imaging (CS-MRI). Latest deep networks for CS-MRI …