Seong G Kong

Professor

Sejong University

South Korea

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Seong G Kong is a Professor at Sejong University in South Korea. His research focuses on advanced imaging techniques, particularly in hyperspectral and infrared imaging, with recent articles addressing topics such as object detection, image denoising, and marine velocity field recovery. He is also involved in developing methods for nondestructive testing of materials and enhancing visual data completion.

Seong G Kong

Research Interests

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Articles (27)

Multi-fractional spatial-spectral constraint for detecting sub-mosaic objects in snapshot spectral imaging

Fusion of polarization degree and thermal parameters for enhanced nondestructive testing of coated metals

Polarization-Guided unsupervised convection networks for marine velocity field recovery

Transductive gradient injection for improved hyperspectral image denoising

Color-aware fusion of nighttime infrared and visible images

Guided Feature Fusion: Zero-Shot Framework for Hyperspectral Image Denoising

Subsurface Defect Detection in Carbon Fiber-Reinforced Plastics Using Infrared Polarization Imaging

U²PNet: An Unsupervised Underwater Image-Restoration Network Using Polarization

Deep Learning for Abnormal Human Behavior Detection in Surveillance Videos—A Survey

Sequential Learning of Flame Objects Sorted by Size for Early Fire Detection in Surveillance Videos

Deep neural networks with adaptive solution space for inverse design of multilayer deep-etched grating

Enhancing Visual Data Completion with Pseudo Side Information Regularization

Few-Sample Anomaly Detection in Industrial Images With Edge Enhancement and Cascade Residual Feature Refinement

Navigating Uncertainty: Semantic-Powered Image Enhancement and Fusion

Physics-Driven Multispectral Filter Array Pattern Optimization and Hyperspectral Image Reconstruction

Polarization-Driven Solution for Mitigating Scattering and Uneven Illumination in Underwater Imagery

Swarm Optimization of 2-D Metasurface Structure for Low-Crosstalk LWIR Filter Arrays

Multimodal feature fusion for illumination-invariant recognition of abnormal human behaviors

Laplacian Pyramid Fusion Network With Hierarchical Guidance for Infrared and Visible Image Fusion

An Iterative Learning Scheme with Binary Classifier for Improved Event Detection in Surveillance Video

Key-Frame Extraction for Reducing Human Effort in Object Detection Training for Video Surveillance

Spectral Super-Resolution Based on Dictionary Optimization Learning via Spectral Library

When Laplacian Scale Mixture Meets Three-Layer Transform: A Parametric Tensor Sparsity for Tensor Completion

Multilayer Sparsity-Based Tensor Decomposition for Low-Rank Tensor Completion

Object Tracking in Hyperspectral-Oriented Video with Fast Spatial-Spectral Features

Multisensor Image Fusion for Automated Detection of Defects in Printed Circuit Boards

A Micro-Polarizer Array Configuration Design Method for Division of Focal Plane Imaging Polarimeter

Collaborators (3)

Wenzhi Liao

Jonathan Chan

Lipo Wang

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