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Heechul Jung

Kyungpook National University

South Korea

Research Interests

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Professors in South Korea Professors in Deep Learning Deep Learning professors in South Korea

Articles (31)

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Collaborators (5)

Sangseok Yun

Pusan National University

SOUTH KOREA

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Dong-Woo Lim

Changwon National University

SOUTH KOREA

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Hyeonuk Lee

Korea Electrotechnology Research Institute

SOUTH KOREA

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Il-Min Kim

Professor

Queen's University

CANADA

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Abdul Rehman

Research Professor

Jeonju University

SOUTH KOREA

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Heechul Jung

Research Interests

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Articles (31)

Worst-Case Robust Training Design for Correlated MIMO Channels in the Presence of Colored Interference

Generative-Diffusion-Model-Based Deep-Learning Framework for Remaining Useful Life Prediction

NMAP-Net: Deep-Learning-Aided Near-Field Multibeamforming Design and Antenna Position Optimization for XL-MIMO Communications

Metaheuristics for pruning convolutional neural networks: A comparative study

Joint Transmit Power and Power-Splitting Optimization for SWIPT in D2D-Enabled Cellular Networks with Energy Cooperation

SmartFormer: Graph-based transformer model for energy load forecasting

A Novel VLM-Guided Diffusion Model for Remote Sensing Image Super-Resolution

CaMPASS-Net: A Deep Learning Framework on Capacity Maximization for MIMO Pinching Antenna Systems in IoT

Corrections to “DASK-Net: A Lightweight Dual-Attention Selective Kernel Network for Efficient Dense Prediction in Remote Sensing Imagery”

DASK-Net: A Lightweight Dual-Attention Selective Kernel Network for Efficient Dense Prediction in Remote Sensing Imagery

Benchmarking Real-World Many-Objective Problems: A Problem Suite With Baseline Results

Robust Transceiver Design for Correlated MIMO Interference Channels in the Presence of CSI Errors under General Power Constraints

On the LoRa Modulation for IoT: Preamble Designs for Channel Estimation With Single- and Multi-Chirp Transmission Strategies

Smart city fire surveillance: A deep state‐space model with intelligent agents

OCR-Diff: A Two-Stage Deep Learning Framework for Optical Character Recognition Using Diffusion Model in Industrial Internet of Things

Entropy‐based sampling for efficient training of deep learning on CNC machining dataset

Multi-Objective Evolutionary Hybrid Deep Learning for energy theft detection

RobuT-Net: Dual-CNN-Based Robust Training Sequence Design for IoT Systems

Deep-Learning-Based Robust Channel Estimation for MIMO IoT Systems

Corrections to “LoRa Preamble Detection With Optimized Thresholds”

Corrections to “MIMO-LoRa for High-Data-Rate IoT: Concept and Precoding Design”

Enhanced Non-Maximum Suppression for the Detection of Steel Surface Defects

An effective ensemble framework for Many-Objective optimization based on AdaBoost and K-means clustering

LoRa Preamble Detection With Optimized Thresholds

Probabilistic Classification Method of Spiking Neural Network Based on Multi-Labeling of Neurons

User Grouping, Precoding Design, and Power Allocation for MIMO-NOMA Systems

Transmit Power Adaptation for D2D Communications Underlaying SWIPT-Based IoT Cellular Networks

A New Index Modulation for LoRa

An Optimized Multi-Organ Cancer Cells Segmentation for Histopathological Images Based on CBAM-Residual U-Net

Efficient Demodulation Algorithms for MIMO-LoRa

Many-Objective Real-World Engineering Problems: A Comparative Study of State-of-the-Art Algorithms

Collaborators (5)

Sangseok Yun

Dong-Woo Lim

Hyeonuk Lee

Il-Min Kim

Abdul Rehman

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