most citedAn Effective GCN-based Hierarchical Multi-label classification for Protein Function Prediction

7 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2023

Central Angle Optimization for 360-degree Holographic 3D Content

Hakdong Kim, Minsung Yoon, Cheongwon Kim

In this study, we propose a method to find an optimal central angle in deep learning-based depth map estimation used to produce realistic holographic content. The acquisition of RG…

cs.CV2023

A novel approach for holographic 3D content generation without depth map

Hakdong Kim, Minkyu Jee, Yurim Lee +3

In preparation for observing holographic 3D content, acquiring a set of RGB color and depth map images per scene is necessary to generate computer-generated holograms (CGHs) when u…

cs.NE2021★ 1 cited

Genetic Algorithm for Constrained Molecular Inverse Design

Yurim Lee, Gydam Choi, Minsung Yoon +1

A genetic algorithm is suitable for exploring large search spaces as it finds an approximate solution. Because of this advantage, genetic algorithm is effective in exploring vast a…

cs.AI2021★ 7 cited

An Effective GCN-based Hierarchical Multi-label classification for Protein Function Prediction

Kyudam Choi, Yurim Lee, Cheongwon Kim +1

We propose an effective method to improve Protein Function Prediction (PFP) utilizing hierarchical features of Gene Ontology (GO) terms. Our method consists of a language model for…

cs.CV2021

Deep Learning-based High-precision Depth Map Estimation from Missing Viewpoints for 360 Degree Digital Holography

Hakdong Kim, Heonyeong Lim, Minkyu Jee +5

In this paper, we propose a novel, convolutional neural network model to extract highly precise depth maps from missing viewpoints, especially well applicable to generate holograph…