Chanjun Chun

Assistant Prof.

Chosun University

South Korea

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About

Chanjun Chun is an Assistant Professor at Chosun University in South Korea. His research focuses on advanced topics in wireless communication, speaker recognition, and sound event localization, with recent publications exploring innovative techniques in these areas. He has also delved into generative models for webtoon creation and applications of synthetic data in various domains, highlighting the intersection of technology and creativity in his work.

Articles (13)

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2025

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2023

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2022

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2021

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2020

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2020

Collaborators (4)

Seong-Yong Moon

Professor

Chosun University College of Dentistry and Graduate School of Dentistry

SOUTH KOREA

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Yonggang Kim

Kongju National University

SOUTH KOREA

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Wooyeol Choi

SOUTH KOREA

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Pulok Tarafder

Howard University

UNITED STATES

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Chanjun Chun

Research Interests

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About

Articles (13)

Channel Estimation in 5G-and-Beyond Wireless Communication: A Comprehensive Survey

Contrastive Speaker Representation Learning with Hard Negative Sampling for Speaker Recognition

Static Sound Event Localization and Detection Using Bipartite Matching Loss for Emergency Monitoring

A Pre-Training Framework Based on Multi-Order Acoustic Simulation for Replay Voice Spoofing Detection

A Study on Generating Webtoons Using Multilingual Text-to-Image Models

Conformer-Based Dental AI Patient Clinical Diagnosis Simulation Using Korean Synthetic Data Generator for Multiple Standardized Patient Scenarios

Sound Event Localization and Detection Using Imbalanced Real and Synthetic Data via Multi-Generator

Effective Zero-Shot Multi-Speaker Text-to-Speech Technique Using Information Perturbation and a Speaker Encoder

A Study on Webtoon Generation Using CLIP and Diffusion Models

Synthetic Data Generator for Solving Korean Arithmetic Word Problem

Detection of Road-Surface Anomalies Using a Smartphone Camera and Accelerometer

Classification and Segmentation of Longitudinal Road Marking using Convolutional Neural Networks for Dynamic Retroreflection Estimation

Configuration-Invariant Sound Localization Technique Using Azimuth-Frequency Representation and Convolutional Neural Networks

Collaborators (4)

Seong-Yong Moon

Yonggang Kim

Wooyeol Choi

Pulok Tarafder

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