Min Ju Kim

Orcid: 0000-0003-0979-9835

According to our database1, Min Ju Kim authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Overcoming Performance Limitation of IGZO FET by iCVD Fluorine Doping.
Proceedings of the IEEE Symposium on VLSI Technology and Circuits 2024, 2024

Occluded Part-aware Graph Convolutional Networks for Skeleton-based Action Recognition.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

2023
Fluxformer: Flow-Guided Duplex Attention Transformer via Spatio-Temporal Clustering for Action Recognition.
IEEE Robotics Autom. Lett., October, 2023

Characterization of attentional event-related potential from REM sleep behavior disorder patients based on explainable machine learning.
Comput. Methods Programs Biomed., June, 2023

2022
Computer-aided hepatocellular carcinoma detection on the hepatobiliary phase of gadoxetic acid-enhanced magnetic resonance imaging using a convolutional neural network: Feasibility evaluation with multi-sequence data.
Comput. Methods Programs Biomed., 2022

2021
Active Learning for Efficient Segmentation of Liver with Convolutional Neural Network-Corrected Labeling in Magnetic Resonance Imaging-Derived Proton Density Fat Fraction.
J. Digit. Imaging, 2021

Deep convolution neural networks to differentiate between COVID-19 and other pulmonary abnormalities on chest radiographs: Evaluation using internal and external datasets.
Int. J. Imaging Syst. Technol., 2021

2019
Analyte Quantity Detection from Lateral Flow Assay Using a Smartphone.
Sensors, 2019

Rectal cancer: Toward fully automatic discrimination of T2 and T3 rectal cancers using deep convolutional neural network.
Int. J. Imaging Syst. Technol., 2019

Multi-Task Learning with a Fully Convolutional Network for Rectum and Rectal Cancer Segmentation.
CoRR, 2019

Reducing the Model Variance of a Rectal Cancer Segmentation Network.
IEEE Access, 2019


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