Search Results for author: Xiaoyu Cui

Found 5 papers, 1 papers with code

Dual-channel Prototype Network for few-shot Classification of Pathological Images

no code implementations14 Nov 2023 Hao Quan, Xinjia Li, Dayu Hu, Tianhang Nan, Xiaoyu Cui

The approach enhances the versatility of prototype representations and elevates the efficacy of prototype networks in few-shot pathological image classification tasks.

Classification Few-Shot Learning +2

Twitter's Agenda-Setting Role: A Study of Twitter Strategy for Political Diversion

no code implementations16 Dec 2022 Yuyang Chen, Xiaoyu Cui, Yunjie Song, Manli Wu

This study verified the effectiveness of Donald Trump's Twitter campaign in guiding agen-da-setting and deflecting political risk and examined Trump's Twitter communication strategy and explores the communication effects of his tweet content during Covid-19 pandemic.

Time Series Time Series Analysis

Global Contrast Masked Autoencoders Are Powerful Pathological Representation Learners

1 code implementation18 May 2022 Hao Quan, Xingyu Li, Weixing Chen, Qun Bai, Mingchen Zou, Ruijie Yang, Tingting Zheng, Ruiqun Qi, Xinghua Gao, Xiaoyu Cui

Based on digital pathology slice scanning technology, artificial intelligence algorithms represented by deep learning have achieved remarkable results in the field of computational pathology.

Computed Tomography (CT) Self-Supervised Learning +1

A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images

no code implementations5 May 2022 Tingting Zheng, Weixing Chen, Shuqin Li, Hao Quan, Qun Bai, Tianhang Nan, Song Zheng, Xinghua Gao, Yue Zhao, Xiaoyu Cui

Inspired by the pathologist's clinical diagnosis process, we propose a weakly supervised deep reinforcement learning framework, which can greatly reduce the time required for network inference.

Knowledge Distillation reinforcement-learning +2

Dynamic radiomics: a new methodology to extract quantitative time-related features from tomographic images

no code implementations1 Nov 2020 Fengying Che, Ruichuan Shi, Jian Wu, Haoran Li, Shuqin Li, Weixing Chen, Hao Zhang, Zhi Li, Xiaoyu Cui

The feature extraction methods of radiomics are mainly based on static tomographic images at a certain moment, while the occurrence and development of disease is a dynamic process that cannot be fully reflected by only static characteristics.

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