Dynamic neural network is an emerging research topic in deep learning. Compared to static
models which have fixed computational graphs and parameters at the inference stage …

Visual attention has become a popular and widely used component for image recognition.
Although various attention-based methods have been proposed and achieved relatively …

An efficient nondestructive testing method is important to inspect the quality of agricultural
products. The material content of tea differs across different picking periods, leading to …

The dynamic neural network (DNN), in contrast to the static counterpart, offers numerous
advantages, such as improved accuracy, efficiency, and interpretability. These benefits stem …

One of the key challenges to the X-ray security check is to detect the overlapped items in
backpacks or suitcases in the X-ray images. Most existing methods improve the robustness …

Cross-technology communication is essential for the Internet of Multimedia Things (IoMT)
applications, enabling seamless integration of diverse media formats, optimized data …

Crowd counting in congested scenarios is an essential yet challenging task in detecting
abnormal crowd for contemporary urban planning. The counting accuracy has been …

The self-attention mechanism (SAM) is widely used in various fields of artificial intelligence
and has successfully boosted the performance of different models. However, current …

Attention mechanisms have shown great success in computer vision. However, the
commonly used global average pooling in some implementations aggregates a three …

Rotating machinery is prone to faults, especially bearing faults. Existing machinery fault
diagnosis methods suffer from low accuracy and poor robustness under actual complex …