Cargando…
Tensor-Based Emotional Category Classification via Visual Attention-Based Heterogeneous CNN Feature Fusion
The paper proposes a method of visual attention-based emotion classification through eye gaze analysis. Concretely, tensor-based emotional category classification via visual attention-based heterogeneous convolutional neural network (CNN) feature fusion is proposed. Based on the relationship between...
Autores principales: | Moroto, Yuya, Maeda, Keisuke, Ogawa, Takahiro, Haseyama, Miki |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180805/ https://www.ncbi.nlm.nih.gov/pubmed/32290175 http://dx.doi.org/10.3390/s20072146 |
Ejemplares similares
-
Few-Shot Personalized Saliency Prediction Based on Adaptive Image Selection Considering Object and Visual Attention†
por: Moroto, Yuya, et al.
Publicado: (2020) -
Prediction of Shooting Events in Soccer Videos Using Complete Bipartite Graphs and Players’ Spatial-Temporal Relations
por: Goka, Ryota, et al.
Publicado: (2023) -
Regularization Meets Enhanced Multi-Stage Fusion Features: Making CNN More Robust against White-Box Adversarial Attacks
por: Zhang, Jiahuan, et al.
Publicado: (2022) -
Deterioration Level Estimation Based on Convolutional Neural Network Using Confidence-Aware Attention Mechanism for Infrastructure Inspection
por: Ogawa, Naoki, et al.
Publicado: (2022) -
Multi-Label Classification in Anime Illustrations Based on Hierarchical Attribute Relationships
por: Lan, Ziwen, et al.
Publicado: (2023)