b'Jun Shi'

research

∙ 08/27/2023

Sparse Sampling Transformer with Uncertainty-Driven Ranking for Unified Removal of Raindrops and Rain Streaks

In the real world, image degradations caused by rain often exhibit a com...

0 Sixiang Chen, et al. ∙

research

∙ 07/05/2023

Multi-Scale Prototypical Transformer for Whole Slide Image Classification

Whole slide image (WSI) classification is an essential task in computati...

0 Saisai Ding, et al. ∙

research

∙ 07/04/2023

H-DenseFormer: An Efficient Hybrid Densely Connected Transformer for Multimodal Tumor Segmentation

Recently, deep learning methods have been widely used for tumor segmenta...

0 Jun Shi, et al. ∙

research

∙ 06/26/2023

Multi-View Attention Learning for Residual Disease Prediction of Ovarian Cancer

In the treatment of ovarian cancer, precise residual disease prediction ...

0 Xiangneng Gao, et al. ∙

research

∙ 06/12/2023

Weakly Supervised Lesion Detection and Diagnosis for Breast Cancers with Partially Annotated Ultrasound Images

Deep learning (DL) has proven highly effective for ultrasound-based comp...

0 Jian Wang, et al. ∙

research

∙ 05/25/2023

Multi-scale Efficient Graph-Transformer for Whole Slide Image Classification

The multi-scale information among the whole slide images (WSIs) is essen...

0 Saisai Ding, et al. ∙

research

∙ 05/04/2023

Spatial and Modal Optimal Transport for Fast Cross-Modal MRI Reconstruction

Multi-modal Magnetic Resonance Imaging (MRI) plays an important role in ...

0 Qi Wang, et al. ∙

research

∙ 04/22/2023

Fast MRI Reconstruction via Edge Attention

Fast and accurate MRI reconstruction is a key concern in modern clinical...

0 Hanhui Yang, et al. ∙

research

∙ 03/13/2023

DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes

Varicolored haze caused by chromatic casts poses haze removal and depth ...

0 Sixiang Chen, et al. ∙

research

∙ 03/08/2023

SANDFORMER: CNN and Transformer under Gated Fusion for Sand Dust Image Restoration

Although Convolutional Neural Networks (CNN) have made good progress in ...

0 Jun Shi, et al. ∙

research

∙ 11/28/2022

A Model-data-driven Network Embedding Multidimensional Features for Tomographic SAR Imaging

Deep learning (DL)-based tomographic SAR imaging algorithms are graduall...

0 Yu Ren, et al. ∙

research

∙ 11/28/2022

Near-filed SAR Image Restoration with Deep Learning Inverse Technique: A Preliminary Study

Benefiting from a relatively larger aperture's angle, and in combination...

0 Xu Zhan, et al. ∙

research

∙ 11/28/2022

Solving 3D Radar Imaging Inverse Problems with a Multi-cognition Task-oriented Framework

This work focuses on 3D Radar imaging inverse problems. Current methods ...

0 Xu Zhan, et al. ∙

research

∙ 09/21/2022

Sar Ship Detection based on Swin Transformer and Feature Enhancement Feature Pyramid Network

With the booming of Convolutional Neural Networks (CNNs), CNNs such as V...

0 Xiao Ke, et al. ∙

research

∙ 08/20/2022

SnowFormer: Scale-aware Transformer via Context Interaction for Single Image Desnowing

Single image desnowing is a common yet challenging task. The complex sno...

2 Sixiang Chen, et al. ∙

research

∙ 06/27/2022

Kernel Attention Transformer (KAT) for Histopathology Whole Slide Image Classification

Transformer has been widely used in histopathology whole slide image (WS...

13 Yushan Zheng, et al. ∙

research

∙ 06/27/2022

Lesion-Aware Contrastive Representation Learning for Histopathology Whole Slide Images Analysis

Local representation learning has been a key challenge to promote the pe...

14 Jun Li, et al. ∙

research

∙ 05/31/2022

Pseudo-Data based Self-Supervised Federated Learning for Classification of Histopathological Images

Computer-aided diagnosis (CAD) can help pathologists improve diagnostic ...

10 Jun Shi, et al. ∙

research

∙ 10/21/2021

A channel attention based MLP-Mixer network for motor imagery decoding with EEG

Convolutional neural networks (CNNs) and their variants have been succes...

0 Yanbin He, et al. ∙

research

∙ 08/16/2021

Causal Incremental Graph Convolution for Recommender System Retraining

Real-world recommender system needs to be regularly retrained to keep wi...

0 Sihao Ding, et al. ∙

research

∙ 08/13/2021

Incremental Learning for Personalized Recommender Systems

Ubiquitous personalized recommender systems are built to achieve two see...

0 Yunbo Ouyang, et al. ∙

research

∙ 08/12/2021

Logit Attenuating Weight Normalization

Over-parameterized deep networks trained using gradient-based optimizers...

0 Aman Gupta, et al. ∙

research

∙ 06/29/2021

Two-Stage Self-Supervised Cycle-Consistency Network for Reconstruction of Thin-Slice MR Images

The thick-slice magnetic resonance (MR) images are often structurally bl...

13 Zhiyang Lu, et al. ∙

research

∙ 06/07/2021

Task-driven Semantic Coding via Reinforcement Learning

Task-driven semantic video/image coding has drawn considerable attention...

0 Xin Li, et al. ∙

research

∙ 05/14/2021

Dual-Attention Residual Network for Automatic Diagnosis of COVID-19

The ongoing global pandemic of Coronavirus Disease 2019 (COVID-19) has p...

0 Jun Shi, et al. ∙

research

∙ 04/16/2021

Histopathology WSI Encoding based on GCNs for Scalable and Efficient Retrieval of Diagnostically Relevant Regions

Content-based histopathological image retrieval (CBHIR) has become popul...

0 Yushan Zheng, et al. ∙

research

∙ 03/31/2021

SRA-LSTM: Social Relationship Attention LSTM for Human Trajectory Prediction

Pedestrian trajectory prediction for surveillance video is one of the im...

0 Yusheng Peng, et al. ∙

research

∙ 01/15/2021

Task-driven Self-supervised Bi-channel Networks Learning for Diagnosis of Breast Cancers with Mammography

Deep learning can promote the mammography-based computer-aided diagnosis...

0 Ronglin Gong, et al. ∙

research

∙ 10/12/2020

Reconstruction of Quantitative Susceptibility Maps from Phase of Susceptibility Weighted Imaging with Cross-Connected Ψ-Net

Quantitative Susceptibility Mapping (QSM) is a new phase-based technique...

6 Zhiyang Lu, et al. ∙

research

∙ 07/21/2020

Balance Scene Learning Mechanism for Offshore and Inshore Ship Detection in SAR Images

This letter proposes a novel Balance Scene Learning Mechanism (BSLM) for...

0 Tianwen Zhang, et al. ∙

research

∙ 06/26/2020

Memory-efficient Embedding for Recommendations

Practical large-scale recommender systems usually contain thousands of f...

1 Xiangyu Zhao, et al. ∙

research

∙ 04/06/2020

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

The pandemic of coronavirus disease 2019 (COVID-19) is spreading all ove...

18 Feng Shi, et al. ∙

research

∙ 03/12/2020

SASL: Saliency-Adaptive Sparsity Learning for Neural Network Acceleration

Accelerating the inference speed of CNNs is critical to their deployment...

0 Jun Shi, et al. ∙

research

∙ 11/04/2019

AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

This paper reviews the AIM 2019 challenge on constrained example-based s...

12 Kai Zhang, et al. ∙

research

∙ 10/16/2019

Reinforced Bit Allocation under Task-Driven Semantic Distortion Metrics

Rapid growing intelligent applications require optimized bit allocation ...

0 Jun Shi, et al. ∙

research

∙ 04/04/2019

Lightweight Image Super-Resolution with Adaptive Weighted Learning Network

Deep learning has been successfully applied to the single-image super-re...

0 Chaofeng Wang, et al. ∙

research

∙ 04/02/2018

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

In the NIPS 2017 Learning to Run challenge, participants were tasked wit...

0 Łukasz Kidziński, et al. ∙

Jun Shi

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