Amanote Research

Amanote Research

    RegisterSign In

Discover open access scientific publications

Search, annotate, share and cite publications


Publications by In-Ha Kim

A Study on the Performance Enhancement of Radar Target Classification Using the Two-Level Feature Vector Fusion Method

Journal of Electromagnetic Engineering and Science
2018English

Related publications

Multimodal Classification Using Feature Level Fusion and SVM

International Journal of Computer Applications
2013English

A Target Tracking Method Based on Feature Fusion

2015English

Feature Level Fusion Using Physical Biometric Traits

International Journal of Biomedical Engineering and Technology
Biomedical Engineering
2018English

Radar Target Classification Technologies

2010English

Dynamic Human Fatigue Detection Using Feature-Level Fusion

Lecture Notes in Computer Science
Computer ScienceTheoretical Computer Science
2008English

Two Step Feature Extraction Method for Microarray Cancer Data Using Support Vector Machines

International Journal of Computer Applications
2014English

Performance Comparison for Radar Target Classification of Monostatic RCS and Bistatic RCS

The Journal of Korean Institute of Electromagnetic Engineering and Science
2010English

A Method of Classification Using Kohonen's Self-Organizing Feature Maps

IEEJ Transactions on Electronics, Information and Systems
Electronic EngineeringElectrical
1995English

A Feature Fusion Approach for Hand Tools Classification

International Journal of Advanced Computer Science and Applications
Computer Science
2017English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2026 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy