Fangyu Liu

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University of Waterloo ∙ University of Cambridge

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DeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation

In this work, we propose an AI-based method that intends to improve the ...
11/01/2020 ∙ by Jia-Hong Huang, et al. ∙ 0 ∙ share

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Self-alignment Pre-training for Biomedical Entity Representations

Despite the widespread success of self-supervised learning via masked la...
10/22/2020 ∙ by Fangyu Liu, et al. ∙ 0 ∙ share

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COMETA: A Corpus for Medical Entity Linking in the Social Media

Whilst there has been growing progress in Entity Linking (EL) for genera...
10/07/2020 ∙ by Marco Basaldella, et al. ∙ 0 ∙ share

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Visual Pivoting for (Unsupervised) Entity Alignment

This work studies the use of visual semantic representations to align en...
09/28/2020 ∙ by Fangyu Liu, et al. ∙ 8 ∙ share

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Upgrading the Newsroom: An Automated Image Selection System for News Articles

We propose an automated image selection system to assist photo editors i...
04/23/2020 ∙ by Fangyu Liu, et al. ∙ 0 ∙ share

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HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs

The hubness problem widely exists in high-dimensional embedding space an...
11/22/2019 ∙ by Fangyu Liu, et al. ∙ 0 ∙ share

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A Strong and Robust Baseline for Text-Image Matching

We review the current schemes of text-image matching models and propose ...
06/04/2019 ∙ by Fangyu Liu, et al. ∙ 0 ∙ share

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Auto-Classification of Retinal Diseases in the Limit of Sparse Data Using a Two-Streams Machine Learning Model

Automatic clinical diagnosis of retinal diseases has emerged as a promis...
08/16/2018 ∙ by C. -H. Huck Yang, et al. ∙ 10 ∙ share

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3D Depthwise Convolution: Reducing Model Parameters in 3D Vision Tasks

Standard 3D convolution operations require much larger amounts of memory...
08/05/2018 ∙ by Rongtian Ye, et al. ∙ 0 ∙ share

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A Novel Hybrid Machine Learning Model for Auto-Classification of Retinal Diseases

Automatic clinical diagnosis of retinal diseases has emerged as a promis...
06/17/2018 ∙ by C. -H. Huck Yang, et al. ∙ 0 ∙ share

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3DCNN-DQN-RNN: A Deep Reinforcement Learning Framework for Semantic Parsing of Large-scale 3D Point Clouds

Semantic parsing of large-scale 3D point clouds is an important research...
07/21/2017 ∙ by Fangyu Liu, et al. ∙ 0 ∙ share

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