Smartphones are now nearly ubiquitous; their numerous built-in sensors enable continuous
measurement of activities of daily living, making them especially well-suited for health …

Human action recognition (HAR) has gained significant attention recently as it can be
adopted for a smart surveillance system in Multimedia. However, HAR is a challenging task …

Nowadays, sensor-equipped mobile devices allow us to detect basic daily activities
accurately. However, the accuracy of the existing activity recognition methods decreases …

Falls are current events that can lead to severe injuries and even accidental deaths among
the population, especially the elderly. Since them usually live alone and their contact with …

This paper presents a new IndRNN-based deep attention model, termed DA-IndRNN, for
skeleton-based action recognition to effectively model the fact that different joints are usually …

Background: Smartphones are now nearly ubiquitous; their numerous built-in sensors
enable continuous measurement of activities of daily living, making them especially well …

Recurrent neural networks (RNNs) have been widely used to solve sequence problems due
to their capability of modeling temporal dependency. Despite the rich varieties of RNN …

In order to improve the style extraction and extraction ability of works of art, a color extraction
method based on color features is proposed. The color feature extraction method is used to …

Considering that the traditional deep learning event extraction method ignores the
correlation between word features and sequence information, it cannot fully explore the …

To solve the problem of intelligent image recognition in classroom behavior, this paper
proposes a fast target detection based on FFmpeg CODEC, extracts MHI‐HOG joint features …