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 …

Many single image super-resolution (SISR) methods that use convolutional neural networks
(CNNs) learn the relationship between low-and high-resolution images directly, without …

Recent years have witnessed the great advances of deep neural networks (DNNs) in light
field (LF) image super-resolution (SR). However, existing DNN-based LF image SR methods …

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

Magnetic resonance imaging (MRI) possesses the unique versatility to acquire images
under a diverse array of distinct tissue contrasts, which makes multicontrast super-resolution …

Landslides refer to occurrences of massive ground movements due to geological (and
meteorological) factors, and can have disastrous impacts on property, economy, and even …

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 …

With the continuous advancement of autonomous driving technology, 3D vehicle detection
has become of widespread interest. The traditional aggregate view object detection (AVOD) …

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 …

Landslides, ubiquitous geological hazards on steep slopes, present formidable challenges
in tropical regions with dense rainforest vegetation, impeding accurate mapping and risk …