activity
20182020
most citedDeepOpht: Medical Report Generation for Retinal Images via Deep Models and Visual Explanation

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

collaborators

5 papers

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.LG2018

Ambient Hidden Space of Generative Adversarial Networks

Xinhan Di, Pengqian Yu, Meng Tian

Generative adversarial models are powerful tools to model structure in complex distributions for a variety of tasks. Current techniques for learning generative models require an ac…

cs.LG2018

Towards Adversarial Training with Moderate Performance Improvement for Neural Network Classification

Xinhan Di, Pengqian Yu, Meng Tian

It has been demonstrated that deep neural networks are prone to noisy examples particular adversarial samples during inference process. The gap between robust deep learning systems…