most citedTRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes

4 citations · 4 across the 1 of their papers we have counts for

collaborators

6 papers

cs.CV20194 cited

TRk-CNN: Transferable Ranking-CNN for image classification of glaucoma, glaucoma suspect, and normal eyes

Tae Joon Jun, Youngsub Eom, Dohyeun Kim +4

In this paper, we proposed Transferable Ranking Convolutional Neural Network (TRk-CNN) that can be effectively applied when the classes of images to be classified show a high corre…

cs.CV2018

Tournament Based Ranking CNN for the Cataract grading

Dohyeun Kim, Tae Joon Jun, Daeyoung Kim +1

Solving the classification problem, unbalanced number of dataset among the classes often causes performance degradation. Especially when some classes dominate the other classes wit…

cs.CV2018

2sRanking-CNN: A 2-stage ranking-CNN for diagnosis of glaucoma from fundus images using CAM-extracted ROI as an intermediate input

Tae Joon Jun, Dohyeun Kim, Hoang Minh Nguyen +2

Glaucoma is a disease in which the optic nerve is chronically damaged by the elevation of the intra-ocular pressure, resulting in visual field defect. Therefore, it is important to…

cs.CV2018

Automated diagnosis of pneumothorax using an ensemble of convolutional neural networks with multi-sized chest radiography images

Tae Joon Jun, Dohyeun Kim, Daeyoung Kim

Pneumothorax is a relatively common disease, but in some cases, it may be difficult to find with chest radiography. In this paper, we propose a novel method of detecting pneumothor…

cs.CV2018

Automated detection of vulnerable plaque in intravascular ultrasound images

Tae Joon Jun, Soo-Jin Kang, June-Goo Lee +6

Acute Coronary Syndrome (ACS) is a syndrome caused by a decrease in blood flow in the coronary arteries. The ACS is usually related to coronary thrombosis and is primarily caused b…

cs.CV2018

ECG arrhythmia classification using a 2-D convolutional neural network

Tae Joon Jun, Hoang Minh Nguyen, Daeyoun Kang +3

In this paper, we propose an effective electrocardiogram (ECG) arrhythmia classification method using a deep two-dimensional convolutional neural network (CNN) which recently shows…