140 citations · 230 across the 11 of their papers we have counts for
11 papers
PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition
Ming Jin, Enwei Zhu, Changde Du +2
Emotion recognition is essential in the diagnosis and rehabilitation of various mental diseases. In the last decade, electroencephalogram (EEG)-based emotion recognition has been i…
Recognizing Nested Entities from Flat Supervision: A New NER Subtask, Feasibility and Challenges
Enwei Zhu, Yiyang Liu, Ming Jin +1
Many recent named entity recognition (NER) studies criticize flat NER for its non-overlapping assumption, and switch to investigating nested NER. However, existing nested NER model…
Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features
Changde Du, Kaicheng Fu, Jinpeng Li +1
Decoding human visual neural representations is a challenging task with great scientific significance in revealing vision-processing mechanisms and developing brain-like intelligen…
Benchmarking Domain Generalization on EEG-based Emotion Recognition
Yan Li, Hao Chen, Jake Zhao +2
Electroencephalography (EEG) based emotion recognition has demonstrated tremendous improvement in recent years. Specifically, numerous domain adaptation (DA) algorithms have been e…
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions
Penghua Zhai, Huaiwei Cong, Gangming Zhao +4
\emph{Objective and Impact Statement}. With the renaissance of deep learning, automatic diagnostic systems for computed tomography (CT) have achieved many successful applications.…
MS-MDA: Multisource Marginal Distribution Adaptation for Cross-subject and Cross-session EEG Emotion Recognition
Hao Chen, Ming Jin, Zhunan Li +3
As an essential element for the diagnosis and rehabilitation of psychiatric disorders, the electroencephalogram (EEG) based emotion recognition has achieved significant progress du…
GREN: Graph-Regularized Embedding Network for Weakly-Supervised Disease Localization in X-ray Images
Baolian Qi, Gangming Zhao, Xin Wei +4
Locating diseases in chest X-ray images with few careful annotations saves large human effort. Recent works approached this task with innovative weakly-supervised algorithms such a…
Investigating Critical Risk Factors in Liver Cancer Prediction
Jinpeng Li, Yaling Tao, Ting Cai
We exploit liver cancer prediction model using machine learning algorithms based on epidemiological data of over 55 thousand peoples from 2014 to the present. The best performance…
Cross Chest Graph for Disease Diagnosis with Structural Relational Reasoning
Gangming Zhao, Baolian Qi, Jinpeng Li
Locating lesions is important in the computer-aided diagnosis of X-ray images. However, box-level annotation is time-consuming and laborious. How to locate lesions accurately with…
Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data
Changde Du, Changying Du, Hao Wang +4
There are threefold challenges in emotion recognition. First, it is difficult to recognize human's emotional states only considering a single modality. Second, it is expensive to m…
Semi-supervised Bayesian Deep Multi-modal Emotion Recognition
Changde Du, Changying Du, Jinpeng Li +3
In emotion recognition, it is difficult to recognize human's emotional states using just a single modality. Besides, the annotation of physiological emotional data is particularly…