Kyung-Tae Kim

TL;DR: In this article, an efficient technique is developed to recognize target type using one-dimensional range profiles using MCS algorithm. But the proposed technique utilizes the multiple signal classification algorithm to generate superresolved range profiles.

TL;DR: This approach can provide efficient features for classification by the combined use of a polar mapping procedure and a well-designed classifier and the resulting feature vectors are able to meet the requirements that efficient features should have: invariance with respect to rotation and scale, small dimensionality, as well as highly discriminative information.

TL;DR: The optical properties of macrophage-targeted theranostic nanoparticles (MacTNP) prepared from a Chlorin e6 (Ce6)-hyaluronic acid (HA) conjugate can be activated by reactive oxygen species (ROS) in macrophages as mentioned in this paper.

TL;DR: New features and a redundancy-free feature selection scheme for discriminating targets from clutter in high-resolution synthetic aperture radar imagery are proposed and well combined with various classical discriminative features.

TL;DR: In this article, the scale and translational-invariant features based on the central moments from the distribution of the 1-D scattering centers on the target were obtained using various techniques such as the inverse fast Fourier transform (IFFT), fast root-multiple signal classification (fast root-MUSIC), total least squares-prony (TLS-Prony), generalised eigenvalues utilising signal subspace eigenvectors (GEESE), and the matrix-pencil (MP) algorithm.