Search Results for author:
Found 6 papers, 4 papers with code
H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation
In this paper, we propose a hybrid densely connected network for tumor segmentation, named H-DenseFormer, which combines the representational power of the Convolutional Neural Network (CNN) and the Transformer structures.
Multi-View Attention Learning for Residual Disease Prediction of Ovarian Cancer
To this end, in this paper, we propose a novel Multi-View Attention Learning (MuVAL) method for residual disease prediction, which focuses on the comprehensive learning of 3D Computed Tomography (CT) images in a multi-view manner.
Description-Enhanced Label Embedding Contrastive Learning for Text Classification
Then, we propose a novel Relation of Relation Learning Network (R2-Net) for text classification, in which text classification and R2 classification are treated as optimization targets.
DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesis
Text-to-image synthesis refers to generating an image from a given text description, the key goal of which lies in photo realism and semantic consistency.
DARNet: Dual-Attention Residual Network for Automatic Diagnosis of COVID-19 via CT Images
The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) poses a serious threat to public health and the economy.
R$^2$-Net: Relation of Relation Learning Network for Sentence Semantic Matching
Sentence semantic matching is one of the fundamental tasks in natural language processing, which requires an agent to determine the semantic relation among input sentences.
