Enhancing behavior classification of children in dynamic interaction scenes through improved DCNN model.

ABSTRACT: The rapid development of society makes people pay more attention to the quality of the environment for children's growth. However, due to the differences of young children, different environments are often needed for cultivation in dynamic interaction scenarios. Therefore, the authors propose an environment creation method for children's behavior classification to improve the quality of children's growth environment. Taking the video data of children for a period of time as input, the encoder and decoder are designed to classify children's behavior and obtain behavior characteristics. After the input image is processed by the backbone network DCNN, two outputs are obtained, which are four times of shallow features and 16 times of high-level features. Aiming at the semantic gap between envi

SUBMITTER: Hao K 

PROVIDER: S-EPMC11622845 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature