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20172020
most citedAlgorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces

2 citations · 4 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2020

VLG-Net: Video-Language Graph Matching Network for Video Grounding

Mattia Soldan, Mengmeng Xu, Sisi Qu +2

Grounding language queries in videos aims at identifying the time interval (or moment) semantically relevant to a language query. The solution to this challenging task demands unde…

cs.CV20202 cited

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

Jia-Hong Huang, Chao-Han Huck Yang, Fangyu Liu +9

In this work, we propose an AI-based method that intends to improve the conventional retinal disease treatment procedure and help ophthalmologists increase diagnosis efficiency and…

cs.CV2019

Synthesizing New Retinal Symptom Images by Multiple Generative Models

Yi-Chieh Liu, Hao-Hsiang Yang, Chao-Han Huck Yang +5

Age-Related Macular Degeneration (AMD) is an asymptomatic retinal disease which may result in loss of vision. There is limited access to high-quality relevant retinal images and po…

cs.CV2018

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

C. -H. Huck Yang, Fangyu Liu, Jia-Hong Huang +6

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. Based on the fact that fun…

cs.CV2018

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

C. -H. Huck Yang, Jia-Hong Huang, Fangyu Liu +5

Automatic clinical diagnosis of retinal diseases has emerged as a promising approach to facilitate discovery in areas with limited access to specialists. We propose a novel visual-…