ScholarWorks@Hanyang University ERICA Campus: Kim, Dai-Gyoung

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Kim, Dai-Gyoung (김대경)

ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)

Research Area: 수학, 응용수학, Mathematics, Applied Mathematics

Tel 031-400-5468
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Wavelet transform:4||Image denoising:3||mixed noise:2||Microscopy:2||Singular value decomposition:2||Contact hole:2||Lens formula:2||Lithography:2||NavierStokes equation:2||resist reflow:2||Viscosity:2||EUVL:2||Noise measurement:2||Noise reduction:2||Digital holography:2||wavelet:2||AWGN:2||Nuclear norm:2||Fresnelet transform:2||EUV:1||Edge enhancing:1||Electron energy distribution function:1||Elongated contact hole:1||Encryption:1||FDTD:1||FPGA:1||Factor analysis:1||Feature extraction:1||Filtered noise:1||Filtering:1||Fractionalorder derivative:1||Fresnel transform:1||Fresnel transforms:1||Fresnelet:1||Fusion estimation:1||Gaussian distribution:1||Gaussian noise:1||High NA:1||IMAGERESTORATION:1||Image denoising:1||Image encryption:1||Image restoration:1||Information data hiding:1||Langmuir probe data:1||Langnmir probe (LP):1||Logical states:1||Low rank minimization:1||Lowrank approximation:1||Mask polarization:1||Mechanical:1||Minimization:1||Minimum mean square error:1||Monte Carlo:1||NOISE REMOVAL:1||Navierstokes equation:1||Noisefiltering method:1||Optical proximity correction:1||Pellicle:1||Probabilistic latent variable model:1||Probabilistic principal component analysis:1||Quantum entanglement:1||Quantum error correction:1||Quantum internet:1||Quantum teleportation:1||REGULARIZATION:1||Residual noise:1||Resist reflow:1||Resist reflow process:1||Resist reow:1||SPARSE:1||Shear wavelet frames:1||Similarity measure:1||Sub45 nm node:1||Subband replacement:1||TOTAL VARIATION MINIMIZATION:1||TRANSFORM:1||Vector diffraction:1||WAVELET SHRINKAGE:1||Wavelet transforms:1||compression:1||contact hole:1||convolution neural network:1||data hiding:1||deep learning:1||design:1||elongated contact hole:1||embdedding:1||extraction:1||generalized probabilistic theories:1||hardware:1||importance sampling:1||impulsive noise:1||internet:1||lithography:1||low rank approximation:1||low rank estimation:1||marginal likelihood:1||mechanical:1||minentropy:1||missing:1||nuclear norm:1||optical proximity correction:1||optimal state discrimination:1||pellicle:1||plasma diagnostics:1||rank minimization:1||residual:1||security:1||similarity measure:1||singular value decomposition:1||stress:1||thermal:1||viscosity:1||22 nm pattern:1||wavelet transform:1||32 nm pattern:1||ALGORITHM:1||ANISOTROPIC DIFFUSION:1||Approximation algorithms:1||Bicubic interpolation:1||Blind data hiding:1||Block mathcing:1||Convolutional neural networks:1||DICTIONARIES:1||DWT:1||Decryption:1||Deep learning:1||Deflection:1||Deformation:1||Denoising:1||Dictionary learning:1||Differentiation method:1||Dimension reduction:1||

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55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269

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