17 citations · 24 across the 3 of their papers we have counts for
6 papers
Semi-Supervised Active Learning with Temporal Output Discrepancy
Siyu Huang, Tianyang Wang, Haoyi Xiong +2
While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming. To lower the cost of dat…
Conversion and Implementation of State-of-the-Art Deep Learning Algorithms for the Classification of Diabetic Retinopathy
Mihir Rao, Michelle Zhu, Tianyang Wang
Diabetic retinopathy (DR) is a retinal microvascular condition that emerges in diabetic patients. DR will continue to be a leading cause of blindness worldwide, with a predicted 19…
Data Dropout: Optimizing Training Data for Convolutional Neural Networks
Tianyang Wang, Jun Huan, Bo Li
Deep learning models learn to fit training data while they are highly expected to generalize well to testing data. Most works aim at finding such models by creatively designing arc…
Instance-based Deep Transfer Learning
Tianyang Wang, Jun Huan, Michelle Zhu
Deep transfer learning recently has acquired significant research interest. It makes use of pre-trained models that are learned from a source domain, and utilizes these models for…
Dilated Deep Residual Network for Image Denoising
Tianyang Wang, Mingxuan Sun, Kaoning Hu
Variations of deep neural networks such as convolutional neural network (CNN) have been successfully applied to image denoising. The goal is to automatically learn a mapping from a…
An ELU Network with Total Variation for Image Denoising
Tianyang Wang, Zhengrui Qin, Michelle Zhu
In this paper, we propose a novel convolutional neural network (CNN) for image denoising, which uses exponential linear unit (ELU) as the activation function. We investigate the su…