This paper proposes a new deep learning model for emotion recognition based on heterogeneous convolutional neural networks (HCNNs) and multimodal factorized ...
In view of this, this paper proposes a new deep learning model for emotion recognition based on heterogeneous convolutional neural networks (HCNNs) and ...
This research paper introduces a unique and innovative method for emotion recognition by integrating heterogeneous convolutional neural networks (CNNs) with ...
Aug 21, 2023 · This research paper introduces a unique and innovative method for emotion recognition by integrating heterogeneous convolutional neural networks ...
Missing: factorized | Show results with:factorized
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Emotion recognition using heterogeneous convolutional neural networks combined with multimodal factorized bilinear pooling. Y Zhang, C Cheng, S Wang, T Xia.
Emotion recognition using heterogeneous convolutional neural networks combined with multimodal factorized bilinear pooling. Yong Zhang, Cheng Cheng, Shuai ...
Jan 10, 2024 · Emotion recognition using heterogeneous convolutional neural networks combined with multimodal factorized bilinear pooling. Biomed. Signal ...
This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, ...
Apr 5, 2023 · Then, the proposed model employed heterogeneous CNNs to extract the convolutional features and fuse them by multimodal factorized bilinear.
Emotion recognition using heterogeneous convolutional neural networks combined with multimodal factorized bilinear pooling. Yong Zhang, Cheng Cheng, Shuai ...