ScholarWorks@Korea University: Lim, Myo taeg

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Lim, Myo taeg (임묘택)

College of Engineering

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Tel 3243
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Finite impulse response (FIR) filter:7||state estimation:5||State estimation:4||Classification:4||Object recognition:4||sensor fusion:4||piezoelectric material:3||HMAX:3||obstacle avoidance:3||PPG:3||convolutional neural network:3||Convolutional neural network:3||particle filter:3||TakagiSugeno (TS) fuzzy systems:3||vehicle dynamics:2||Image processing:2||Bernoulli random process:2||sensor:2||Matching:2||finite impulse response (FIR) filter:2||Visual object tracking:2||Linear matrix inequality (LMI):2||deep learning:2||emotion recognition:2||reinforcement learning:2||vehicle detection:2||indoor localization:2||feature fusion:2||Traffic sign recognition:2||Modified discrete GaussianHermite moment:2||model predictive control:2||neural network:2||Binary descriptor:2||feature extraction:2||Attention mechanism:2||Finite impulse response structure:2||wireless sensor network (WSN):2||Active suspension system:2||path planning:2||physiological signal:2||missing horizon:2||unbiased filtering:2||convolutional neural network (CNN):1||Free space information:1||occupancy grid map:1||incomplete measurement information:1||multitarget tracking:1||Kalman filters:1||multiobjective H:1||IEC 624393:1||linear quadratic Gaussian (LQG) controller:1||quantization:1||Unbiased finite memory estimation (UFME):1||pinch detection:1||timevarying delay:1||Distributed filtering:1||Finite impulse response tracker:1||Dominant orientation:1||Markov jump linear system (MJLS):1||Truetarget decision making:1||Local feature extraction:1||Gabor features:1||Inverse partitioned matrix:1||Obstacle Avoidance:1||Humanoid Robot:1||회피기동:1||Binary dense SIFT flow:1||YOLO:1||Filtering theory:1||Fuzzy control:1||L2  Linfinity filter:1||deeplearning:1||convolutional autoencoder:1||Domain adaptation:1||Shadow detection:1||multichannel LiDAR:1||Observers:1||Neural networks:1||Layout:1||image retrieval:1||track management:1||target tracking:1||covariance estimation:1||Vector mapping descriptors:1||IEEE 1588:1||precision time protocol (PTP):1||finite impulse response (FIR) structure:1||logarithmic quantizer:1||Thermodynamic model:1||automotive sunroof system:1||exponential stability:1||dynamic outputfeedback control:1||Composite particle/finite impulse response (FIR) filter (CPFF):1||Digital phase lockedloop:1||Object detection:1||Patch:1||Horizon group shift (HGS):1||Selfrecovering extended Kalman filter (SREKF):1||Multitarget FIR tracking algorithm (MTFTA):1||Optimal unbiased finite memory filter (OUFMF):1||MDGHM filter:1||Bolting cabin:1||TOF camera:1||Avoidance motion selection:1||3D Panoramic Environment Map:1||Visual Servo:1||Effectiveness Analysis:1||Evasive Maneuvering:1||ultrasonic beacon:1||Galerkin method:1||parallel processing:1||Singular systems:1||Emotion recognition:1||EDPE dataset:1||Action recognition:1||Image deraining:1||sampleddata system:1||Convolution neural network:1||Complex shadow:1||Robots:1||Robot control:1||trajectory optimization:1||Transformers:1||Transforms:1||autonomous driving system:1||Convolutional pooling:1||statistical feature:1||imperfect detection probability:1||road vehicles:1||tracktotrack fusion algorithm:1||Kalman filter:1||track disposition:1||Deep learning:1||halfvehicle suspension system:1||parallel distributed compensation (PDC):1||time synchronization:1||Hinfinity filtering:1||Air condition(A/C):1||l(2)l(8) filtering:1||dissipative filtering:1||dynamic parallel distributed compensation (DPDC):1||Visual object tracking (VOT):1||switching extensible FIR filter bank (SEFFB):1||timevarying input delay:1||Indoor localization:1||ANFISbased FIR filter and OF arbitration (AFOA):1||Hybrid particle/finite impulse response (FIR) filter:1||hybrid regularized particle/extended unbiased finite impulse response (RP/EFIR) filter:1||Preceding vehicle tracking:1||Finite memory tracker (FMT):1||SURF algorithm:1||Nonlinear filter:1||Finite impulse response (FIR) structure:1||Construction robot:1||Bolting control system:1||Construction factory:1||Fuzzy Reasoning:1||swarm robot:1||cooperative robot:1||Lightweight Torpedo:1||mobile robot:1||nonlinear systems:1||weak coupling:1||Haar Wavelets:1||Mechatronics:1||pedestrianaction recognition:1||binary descriptor dense scaleinvariant feature transform (SIFT) flow:1||data preprocessing:1||robot operating system:1||risk map:1||Actuators:1||Velocity control:1||robot control:1||Siamese network:1||vision transformer (ViT):1||semantic segmentation:1||object classification:1||finite impulse response filter:1||short term emotion recognition:1||continuous bagofwords:1||driver healthcare system:1||estimated probability:1||T2TF algorithm:1||optimal subpattern assignment metric:1||Geometric transformation:1||redundancy network:1||Visual object detection:1||binary descriptor:1||distributed hybrid particle/finite impulse response (FIR) filter:1||Fuzzy cruise control:1||Maximum likelihood:1||Adaptive horizon:1||Halfvehicle suspension system:1||Nonlinear systems:1||Frequency estimation:1||Adaptive neuro fuzzy inference system (ANFIS):1||TakagiSugeno (TS) fuzzy neural networks:1||Local path planning:1||Steel beam assembly:1||Tendons:1||Bioinspired:1||encoderdecoder network:1||image restoration:1||guided filter:1||twostream convolutional neural network (CNN):1||Fully convolutional network:1||feature selection:1||Suspensions (mechanical systems):1||input delay approach:1||binary total variation:1||multimodal network:1||Computational modeling:1||Robotics:1||experience replay:1||extended reciprocally convex matrix inequality:1||Feature extraction:1||Max pooling:1||Kmeans:1||sentence classification:1||Linked adaptive neuro fuzzy inference system:1||biosignal distortion detection:1||recursive estimation:1||sensor tracks reliability:1||estimated track history:1||Partial distortion or occlusion:1||Onlinetraining control:1||fuzzy preview control:1||high availability seamless redundancy (HSR):1||adaptive neurofuzzy inference system:1||Home energy management system(HEMS):1||Fuzzy logic system:1||Membership function:1||unbiasedness:1||Finite measurements:1||Gaussian distributed resampling:1||Oriented GaussianHermite moment:1||Hough transform:1||Model predictive stabilization:1||MDGHMSIFT:1||Circular Hough Transform:1||Distortion Correction:1||어뢰음향대항체계:1||TwoStream CNN:1||Sensors:1||IEEE transactions:1||dilated convolution:1||Image dehazing:1||Deconvolution:1||Tires:1||Linear matrix inequalities:1||Shadow removal:1||DRM:1||Mathematical models:1||Lowpass filters:1||Machine learning:1||steering delay:1||Autonomous vehicle:1||Location awareness:1||track compensation:1||Comfort level:1||personal normalization:1||Hybrid filter:1||Image stabilization:1||MSURF:1||SIFT:1||Recurrent neural network:1||AdaBoost:1||recursive equations:1||Demand response(DR):1||Antipinch:1||discrete Wirtingertype inequality:1||discretetime switched neural networks (DSNNs):1||human localization:1||particle filter (PF):1||nonlineofsight (NLOS):1||Maximum likelihood FIR filter (MLFIRF):1||finitememory structure:1||Hinfinity control:1||TakagiSugeno fuzzy Hopfield neural network:1||nonlinear system:1||Horizon group shift:1||Cost monotonicity:1||Colored noises:1||State augmetation:1||Humanoid robot:1||TemplateBased Matching:1||MonteCarlo Simulation:1||몬테카를로 시뮬레이션:1||Wake Search(항적 탐색):1||Loading:1||derain:1||positioninformation feature:1||German traffic sign detection benchmark:1||Delays:1||computer vision:1||shorttime Fourier transform (STFT):1||complexvalued convolutional neural network (CVCNN):1||meta learning:1||deep reinforcement learning:1||machine learning:1||dynamic output feedback control:1||Visualization:1||Crossview geolocalization (CVGL):1||polar transform:1||failure detection:1||torsional loading:1||Radar measurement:1||vehicle tracking:1||trackassociation approach:1||total similarity:1||correct association rate:1||Geometric features:1||power utility automation:1||packet dropout:1||estimation:1||Digital phaselocked loop (DPLL):1||multiobjective synthesis:1||TakagiSugeno (TS) fuzzy model:1||Optical flow:1||nonlinear filter:1||Robotic bolting device:1||TACM:1||경어뢰:1||효과도 분석:1||Kullbackleibler distance:1||Wake Homing Torpedo(항적 추적 어뢰):1||Wake Deflection Angle(항적 초기 발사각):1||comfort level:1||Piezoelectric materials:1||dehaze:1||Road traffic:1||multiple object tracking:1||reidentification:1||road segmentation:1||selfdriving:1||extended dissipativity:1||Global Positioning System:1||actuatorsensor pair:1||onedimensional convolutional neural network:1||Particle filter:1||Target tracking:1||MDGHM:1||language model:1||GH(2) control:1||Electrohydraulic suspension system:1||(Q, S, R)alphadissipativity:1||PFbased membership function adjustment:1||quantization error:1||Mobile robot:1||Multitarget tracking (MTT):1||L2Linfinity filtering:1||Wirtingertype inequality:1||weighted average extended FIR filter bank (WAEFFB):1||Finite impulse response filter:1||Construction automation:1||Complexity measure:1||Avoidance Motion Selection:1||Complexity Measure:1||Wake Modeling(항적 모델링):1||optimal control:1||bimodal structure network:1||stacked sparse autoencoder:1||Robot sensing systems:1||biometric:1||traffic sign detection:1||TakagiSugeno fuzzy system:1||EMG:1||autonomous driving:1||road boundary:1||

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