Violence Recognition Based on Auditory-Visual Fusion of Autoencoder Mapping
In the process of violence recognition, accuracy is reduced due to problems related to time axis misalignment and the semantic deviation of multimedia visual auditory information. Therefore, this paper proposes a method for auditory-visual information fusion based on autoencoder mapping. First, a fe...
Guardado en:
Autores principales: | Jiu Lou, Decheng Zuo, Zhan Zhang, Hongwei Liu |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
MDPI AG
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/4ba6c819a8f547abb7858b9008326632 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Auditory Working Memory Explains Variance in Speech Recognition in Older Listeners Under Adverse Listening Conditions
por: Kim S, et al.
Publicado: (2020) -
A facial expression recognition method based on face texture feature fusion
por: Tingting GAO, et al.
Publicado: (2021) -
Industry 4.0-Oriented Deep Learning Models for Human Activity Recognition
por: Saeed Mohsen, et al.
Publicado: (2021) -
Deep Large Margin Nearest Neighbor for Gait Recognition
por: Xu Wanjiang
Publicado: (2021) -
Multi-Run Concrete Autoencoder to Identify Prognostic lncRNAs for 12 Cancers
por: Abdullah Al Mamun, et al.
Publicado: (2021)