output
20202024
most citedGM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition

63 citations

16 papers

eess.IV202229 cited

MouseGAN++: Unsupervised Disentanglement and Contrastive Representation for Multiple MRI Modalities Synthesis and Structural Segmentation of Mouse Brain

Ziqi Yu, Xiaoyang Han, Shengjie Zhang +3

Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding th…

cs.SD202263 cited

GM-TCNet: Gated Multi-scale Temporal Convolutional Network using Emotion Causality for Speech Emotion Recognition

Jia-Xin Ye, Xin-Cheng Wen, Xuan-Ze Wang +5

In human-computer interaction, Speech Emotion Recognition (SER) plays an essential role in understanding the user's intent and improving the interactive experience. While similar s…

cs.CV202262 cited

When Age-Invariant Face Recognition Meets Face Age Synthesis: A Multi-Task Learning Framework and A New Benchmark

Zhizhong Huang, Junping Zhang, Hongming Shan

To minimize the impact of age variation on face recognition, age-invariant face recognition (AIFR) extracts identity-related discriminative features by minimizing the correlation b…

eess.IV202213 cited

Denoising of 3D MR images using a voxel-wise hybrid residual MLP-CNN model to improve small lesion diagnostic confidence

Haibo Yang, Shengjie Zhang, Xiaoyang Han +4

Small lesions in magnetic resonance imaging (MRI) images are crucial for clinical diagnosis of many kinds of diseases. However, the MRI quality can be easily degraded by various no…

math.DS2022

Analytic Investigation for Spatio-temporal Patterns Propagation in Spiking Neural Networks

Ning Hua, Xiangnan He, Wenlian Lu +1

Based upon the moment closure approach, a Gaussian random field is constructed to quantitatively and analytically characterize the dynamics of a random point field. The approach pr…

cs.CL202140 cited

Improving Entity Linking through Semantic Reinforced Entity Embeddings

Feng Hou, Ruili Wang, Jun He +1

Entity embeddings, which represent different aspects of each entity with a single vector like word embeddings, are a key component of neural entity linking models. Existing entity…