Gun-Woo Kim

Assistant Professor

Gyeongsang National University

South Korea

Research Interests

Explore related searches

Professors in South Korea Professors in Medical Imaging Medical Imaging professors in South Korea

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Gun-Woo Kim is an Assistant Professor at Gyeongsang National University in South Korea. His research areas include crime risk analysis, safety systems for the visually impaired, context-aware medical entity recognition, and conversational recommender systems. He has published multiple articles focused on leveraging advanced technologies such as GIS, LiDAR, and large language models to enhance various applications in healthcare and safety.

Articles (10)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2024

Year:

2024

Year:

2023

Collaborators (1)

Hyeri Seok

Yeungnam University Medical Center

SOUTH KOREA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Gun-Woo Kim

Research Interests

Explore related searches

Contact this professor

About

Articles (10)

Crime Risk Analysis and Safety Facility Location Selection Exploiting GIS based on CPTED

Distance Measurement and Obstacle Avoidance System based on 2D LiDAR-Monocular Camera for Safe Walking of Visually Impaired People

COMCARE: A Collaborative Ensemble Framework for Context-Aware Medical Named Entity Recognition and Relation Extraction

Extracting Implicit User Preferences in Conversational Recommender Systems Using Large Language Models

PSR: A Dual-Level Learning Framework for Patching Sequential Recommendation to Capture Local Preference Transitions

Adaptive Stacking Ensemble Techniques for Early Severity Classification of COVID-19 Patients

A Multi-Head Cross Attention-based Skin Lesion Classification Model Exploiting Multimodal Data

Improving Rebar Twist Prediction Exploiting Unified-Channel Attention-Based Image Restoration and Regression Techniques

Health-AutoML: An Automatic Adaptive Multi-Layer Stacking Ensemble Learning Framework for Analyzing Healthcare Data

Enhancing Rebar Endpoint Detection Performance through High-Resolution Rebar Image Generation with SRPAttention-GAN

Collaborators (1)

Hyeri Seok

Make your next move.