CAU Scholar's Space: Hong, Byung-Woo

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Hong, Byung-Woo (홍병우)

소프트웨어대학 (AI학과)

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Tel 02-820-5842
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Training:4||Cardiac MRI:4||Segmentation:4||deep learning:3||Left Ventricle Segmentation:3||Adaptive regularization:3||Image segmentation:3||stochastic gradient descent:3||image registration:3||Optimization:3||Deep learning:3||unsupervised learning:3||coronary CTA:2||Image registration:2||decomposition:2||Optical Flow:2||Classification:2||Anisotropic diffusion:2||Stochastic gradient descent:2||segmentation:2||Task analysis:2||Total Variation:2||Data models:2||Adaptive Regularization:2||motion estimation:2||Neural networks:2||image segmentation:2||myocardial perfusion SPECT:2||Variational framework:2||ScaleSpace:2||superpixel:2||optical flow:2||Evaluation system:1||Face recognition:1||Fourier convolutional neural network:1||Generative adversarial network:1||Generative adversarial networks:1||HuberHuber Model:1||Image Decomposition:1||Image classification:1||Image denoising:1||Image neighborhood:1||Image reconstruction:1||Imagetoimage translation:1||Implicit shape prior:1||Incremental Learning:1||Isotropic diffusion:1||Kernel:1||Knowledge distillation:1||Left Ventricle:1||Left ventricle:1||Level Set:1||Level set function:1||Level set methods:1||Linear programming:1||Local phase:1||Loss measurement:1||MDCT:1||Magnetic resonance imaging:1||Marching Cubes:1||Motion Estimation:1||Multiobjective optimization:1||Multiphase:1||Mumford–Shah model:1||MumfordShah:1||MumfordShah energy functional:1||Mumfordshah algorithm:1||Mutual information:1||Noise injection:1||Noise measurement:1||Nonlocal means:1||Nonlinear registration:1||Optical flow:1||Optimization methods:1||Predictive models:1||Principal component analysis:1||Prior shape knowledge:1||Proximal Gradient Method:1||Random kernel:1||Rotationinvariant:1||Scalespace:1||Scenariobased evaluation system:1||Semantic Segmentation:1||Sensor Fusion:1||Shape analysis:1||Shape descriptor:1||Shape matching:1||Shape statistics:1||Stochastic processes:1||Total variation:1||Ultrasound imaging:1||Uncertainty:1||Unsupervised segmentation:1||Variational methods:1||Visual Learning:1||Volumepreserving constraint:1||Warping:1||Wasserstein distance:1||Weaklysupervised learning:1||active contours:1||adaptive regularity:1||alternating optimization:1||anatomical territories:1||angiocardiography:1||anisotropic diffusion:1||anisotropic scalespace:1||artificial intelligence:1||bias field estimation:1||biomedical image processing:1||clustering:1||coherence enhancement:1||computerised tomography:1||conjugate gradient:1||continual learning:1||contour map:1||cosine similarity:1||curvilinear structure enhancement:1||data trimming:1||deep learning optimization:1||dermoscopy:1||diseases:1||distance:1||expectation minimization:1||fewshot image classification:1||full field digital mammography:1||generative adversarial networks:1||gradientbased metalearning:1||hair removal:1||hierarchical:1||hierarchical segmentation:1||image classification:1||information bottleneck:1||initial contour problem:1||integral invariant:1||integral invariants:1||isocontour:1||label noise:1||large deformation diffeomorphic metric mapping:1||learning rate annealing:1||learning via scale space:1||level set:1||level set evolution without reinitialization:1||level sets:1||local optimum problem:1||local orientation:1||local phase:1||machine learning:1||mammographic breast density:1||mass detection:1||medical image processing:1||medical imaging:1||metric:1||model agnostic metalearning:1||multimodal imagetoimage translation:1||multimodality image registration:1||multimodal image registration:1||network optimization:1||neural networks:1||neural tangent kernel:1||occlusion:1||organ volume:1||orthogonal gradient descent:1||orthogonal projection:1||photometric consistency:1||preprocessing:1||prior statistics:1||proximal algorithm:1||quantitative measure:1||recursive superpixel:1||regularization:1||residual smoothing:1||scale invariance:1||scale invariant:1||secondorder gradient:1||selfsupervision:1||shape:1||shape descriptor:1||shape distance:1||shape matching:1||shape retrieval:1||skin lesion classification:1||smooth regularization:1||spatial domains:1||spatial transcriptomics:1||split:1||structure tensor:1||texture:1||thyroid:1||tissue architecture:1||tissue heterogeneity:1||topographic representation:1||tracking:1||ultrasound:1||unsupervised optical flow estimation:1||variational framework:1||video analysis:1||warping:1||weightdecay:1||바이오인식:1||시나리오기반 평가시스템:1||얼굴인식:1||3D imaging:1||평가시스템:1||ADMM:1||Active contour:1||Adaptation models:1||Adaptive minibatch size:1||Biological neural networks:1||Biometric:1||Blind ensemble:1||Cardiac anatomical segmentation:1||Cardiac disease:1||Cardiac magnetic resonance image (MRI) segmentation:1||Catastrophic forgetting:1||ChanVese:1||ChanVese algorithm:1||Coarsetofine training:1||Computational modeling:1||Computer science:1||Convex Optimization:1||Convolutional Neural Network:1||Coordinate descent:1||Coronary CT angiography (CTA):1||Deep Learning:1||Deep learning application:1||Deep network optimization:1||Deep neural network:1||Deformable Template Matching:1||Denoising:1||Depth completion:1||Digital mammography:1||Dual shape constraint:1||Energy optimization:1||Euclidean distance:1||

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