Image restoration (IR) has been an indispensable and challenging task in the low-level
vision field, which strives to improve the subjective quality of images distorted by various …

Hazy images captured under ill-posed scenarios with scattering medium (ie haze, fog, or
smoke) are contaminated in visibility. Inevitably, these images are further degraded by …

Weakly supervised video anomaly detection is generally formulated as a multiple instance
learning (MIL) problem, where an anomaly detector learns to generate frame-level anomaly …

Using high-fidelity image compression makes it possible to transmit remote-sensing images
in real-time. Nevertheless, existing lossy remote-sensing image compression (RSIC) …

Multimodal sentiment analysis (MSA) is important for quickly and accurately understanding
people's attitudes and opinions about an event. However, existing sentiment analysis …

Fluorescence microscopes are indispensable tools for the life science research community.
Nevertheless, the presence of optical component limitations, coupled with the maximum …

In image denoising, deep convolutional neural networks (CNNs) can obtain favorable
performance on removing spatially invariant noise. However, many of these networks cannot …

Sparse random mode decomposition (SRMD) is a decomposition approach established by
combining sparse random feature model with clustering algorithm. It is not subject to the …

Dropout is a mechanism to prevent deep neural networks from overfitting and improving
their generalization. Random dropout is the simplest method, where nodes are randomly …

The Internet of Things (IoT) has become very popular during the last decade by providing
new solutions to modern industry and to entire societies. At the same time, the rise of the …