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Bumshik Lee (이범식)
Bumshik Lee (이범식)
Korea Institute of Energy Technology (KENTECH)
Verified email at kentech.ac.kr - Homepage
Title
Cited by
Cited by
Year
MRI Segmentation and Classification of Human Brain using Deep Learning for Diagnosis of Alzheimer’s Disease: A Survey
N Yamanakkanavar, JY Choi, Lee, B Lee
Sensors 20 (10), 2020
2732020
A novel fast CU encoding scheme based on spatiotemporal encoding parameters for HEVC inter coding
S Ahn, B Lee, M Kim
IEEE Transactions on Circuits and Systems for Video Technology 25 (3), 422-435, 2015
1702015
Combining LSTM Network Ensemble via Adaptive Weighting for Improved Time Series Forecasting
JY Choi, B Lee
Mathematical Problems in Engineering 2018 (1), 1-8, 2018
1682018
Automatic Segmentation of Brain MRI using a Novel Patch-wise U-net Deep Architecture
B Lee, N Yamanakkanavar, JY Choi
Plos One 15 (8), 2020
1172020
A Frame-level Rate Control Scheme based on Texture and Non-texture Rate Models for High Efficiency Video Coding
B Lee, M Kim, TQ Nguyen
IEEE Transactions on Circuits and Systems for Video Technology 24 (3), 465-479, 2014
1042014
Method for encoding and decoding video signal, and apparatus therefor
KOO Moonmo, S Yea, K Kim, LEE Bumshik
US Patent App. 15/565,823, 2018
902018
Using Blockchain for Improved Video Integrity Verification
S Ghimire, JY Choi, B Lee
IEEE Transactions on Multimedia 22 (1), 108-121, 2020
842020
Combining of Multiple Deep Networks via Ensemble Generalization Loss, based on MRI Images, for Alzheimer's Disease Classification
JY Choi, B Lee
IEEE Signal Processing Letters 27 (1), 206-210, 2020
792020
Ensemble of Deep Convolutional Neural Networks with Gabor Face Representations for Face Recognition
JY Choi, B Lee
IEEE Transactions on Image Processing 29 (1), 3270 - 3281, 2020
782020
Modeling rates and distortions based on a mixture of Laplacian distributions for inter-predicted residues in quadtree coding of HEVC
B Lee, M Kim
IEEE Signal Processing Letters 18 (10), 571-574, 2011
732011
A novel M-SegNet with global attention CNN architecture for automatic segmentation of brain MRI
N Yamanakkanavar, B Lee
Computers in Biology and Medicine 136, 104761, 2021
612021
CNN Models Performance Analysis on MRI images of OASIS dataset for distinction between Healthy and Alzheimer's patient
B Khagi, B Lee, JY Pyun, GR Kwon
2019 International Conference on Electronics, Information, and Communication …, 2019
612019
Using deep CNN with data permutation scheme for classification of Alzheimer's disease in structural magnetic resonance imaging (sMRI)
B Lee, W Ellahi, JY Choi
IEICE TRANSACTIONS on Information and Systems 102 (7), 1384-1395, 2019
602019
Video encoding method for encoding division block, video decoding method for decoding division block, and recording medium for implementing the same
Munchurl Kim, Bumshik Lee, Jae Il Kim, Chang
EP Patent 2,400,763, 2011
52*2011
Method and apparatus for coefficient induced intra prediction in image coding system
J Hyeongmoon, B Lee, S Yea
US Patent 10,819,987, 2020
382020
Using a patch-wise M-net convolutional neural network for tissue segmentation in brain MRI images
N Yamanakkanavar, B Lee
IEEE Access 8, 120946-120958, 2020
382020
GBST: Separable transforms based on line graphs for predictive video coding
HE Egilmez, YH Chao, A Ortega, B Lee, S Yea
2016 IEEE International Conference on Image Processing (ICIP), 2375-2379, 2016
382016
No-reference PSNR estimation for HEVC encoded video
B Lee, M Kim
IEEE Transactions on Broadcasting 59 (1), 20-27, 2013
382013
An All-zero Block Detection Scheme for Low-Complexity HEVC Encoders
B Lee, J Jung, M Kim
IEEE Transactions on Multimedia 17 (7), 1257-1268, 2016
352016
Method for encoding/decoding block information using quad tree, and device for using same
J Kim, HY Kim, SY Jeong, B Lee
US Patent App. US 13/877,503, 2013
35*2013
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Articles 1–20