With the rapid development of object detection, it is widely used in many scenes and
images. However, the dense arrangement of objects with different dimensions, orientations …

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

K-means is a fundamental clustering algorithm widely used in both academic and industrial
applications. Its popularity can be attributed to its simplicity and efficiency. Studies show the …

The few-shot classification (FSC) task aims to classify data with limited labeled examples
across different categories. Typically, researchers pre-train a feature extractor using base …

Face recognition has long been an active research area in the field of artificial intelligence,
particularly since the rise of deep learning in recent years. In some practical situations, each …

As the core of the Sparseland, dictionary learning has represented excellent performances
in many fields, such as pattern recognition, fault diagnosis, noise reduction, image …

Many methods based on data and model analysis have been proposed to overcome the
adverse effect of poses, occlusion, and illumination on face recognition. Frontal face …

In recent decades, falls have posed multiple critical health issues, especially for the older
population, with their emerging growth. Recent research has shown that a wrist-based fall …

Conventional convergence analysis on mini-batch learning is usually based on the
stochastic gradient concept, in which we assume that the training data are presented in a …

To navigate in space, it is important to predict headings in real-time from neural responses in
the brain to vestibular and visual signals, and the ventral intraparietal area (VIP) is one of the …