most citedDeep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition

7 citations · 7 across the 1 of their papers we have counts for

collaborators

6 papers

cs.CV2019

Joint Architecture and Knowledge Distillation in CNN for Chinese Text Recognition

Zi-Rui Wang, Jun Du

The technique of distillation helps transform cumbersome neural network into compact network so that the model can be deployed on alternative hardware devices. The main advantages…

cs.LG20197 cited

Deep Fusion: An Attention Guided Factorized Bilinear Pooling for Audio-video Emotion Recognition

Yuanyuan Zhang, Zi-Rui Wang, Jun Du

Automatic emotion recognition (AER) is a challenging task due to the abstract concept and multiple expressions of emotion. Although there is no consensus on a definition, human emo…

cs.CV2018

Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition

Zi-Rui Wang, Jun Du, Jia-Ming Wang

Recently, the hybrid convolutional neural network hidden Markov model (CNN-HMM) has been introduced for offline handwritten Chinese text recognition (HCTR) and has achieved state-o…

cs.CV2018

Parsimonious HMMs for Offline Handwritten Chinese Text Recognition

Wenchao Wang, Jun Du, Zi-Rui Wang

Recently, hidden Markov models (HMMs) have achieved promising results for offline handwritten Chinese text recognition. However, due to the large vocabulary of Chinese characters w…

cs.CV2018

DenseRAN for Offline Handwritten Chinese Character Recognition

Wenchao Wang, Jianshu Zhang, Jun Du +2

Recently, great success has been achieved in offline handwritten Chinese character recognition by using deep learning methods. Chinese characters are mainly logographic and consist…

cs.SD2018

Attention Based Fully Convolutional Network for Speech Emotion Recognition

Yuanyuan Zhang, Jun Du, Zirui Wang +1

Speech emotion recognition is a challenging task for three main reasons: 1) human emotion is abstract, which means it is hard to distinguish; 2) in general, human emotion can only…