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Search: "[ keyword: Machine Learning ]" (57)
Ensemble Learning of Region Based Classifiers
Sung Ha Choi , Byung Woo Lee , Ji Hoon Yang The KIPS Transactions:PartB ,
Vol. 14, No. 4, pp. 303-310,
Aug.
2007
10.3745/KIPSTB.2007.14.4.303

A Survey of Phishing Campaign Trends and the Classification of Detection Techniques
Ji-Hoon Park, Sang-Hoon Choi, Ki-Woong Park The Transactions of the Korea Information Processing Society,
Vol. 14, No. 3, pp. 149-160,
Mar.
2025
https://doi.org/10.3745/TKIPS.2025.14.3.149
Keywords: Phishing Campaign, Phishing Detection, Machine Learning, LLM, feature extraction

Keywords: Phishing Campaign, Phishing Detection, Machine Learning, LLM, feature extraction
Development of a Model for Predicting the Severity of Traffic Accidents and Analysis of Accident Factors based on Machine Learning
Kim Jung Hyuk, Cho Nam Wook The Transactions of the Korea Information Processing Society,
Vol. 14, No. 2, pp. 72-81,
Feb.
2025
https://doi.org/10.3745/TKIPS.2025.14.2.72
Keywords: Machine Learning, Big data, Traffic Accident, Severity Prediction, Accident Factors

Keywords: Machine Learning, Big data, Traffic Accident, Severity Prediction, Accident Factors
Research on Evaluation Methods for GPR-SEM Prediction Models
Moon Kyung-Yeol, Park Kun-Uk The Transactions of the Korea Information Processing Society,
Vol. 14, No. 1, pp. 14-20,
Jan.
2025
https://doi.org/10.3745/TKIPS.2025.14.1.14
Keywords: Machine Learning, Gaussian Proces Regression, GPR-SEM, Model Evaluation Method, Small-dataset

Keywords: Machine Learning, Gaussian Proces Regression, GPR-SEM, Model Evaluation Method, Small-dataset
Clustering-based Model Compression Method for Deep Neural Networks
Byungchul Chae, Seonyeong Heo The Transactions of the Korea Information Processing Society,
Vol. 13, No. 11, pp. 585-589,
Nov.
2024
https://doi.org/10.3745/TKIPS.2024.13.11.585
Keywords: On-device Machine Learning, Model Compression, Kernel Clustering

Keywords: On-device Machine Learning, Model Compression, Kernel Clustering
Development of an AutoML Web Platform for Text Classification Automation
Ha-Yoon Song, Jeon-Seong Kang, Beom-Joon Park, Junyoung Kim, Kwang-Woo Jeon, Junwon Yoon, Hyun-Joon Chung The Transactions of the Korea Information Processing Society,
Vol. 13, No. 10, pp. 537-544,
Oct.
2024
https://doi.org/10.3745/TKIPS.2024.13.10.537
Keywords: Text Classification, Automated Machine Learning (AutoML), web platform, Natural Language Processing, H2O

Keywords: Text Classification, Automated Machine Learning (AutoML), web platform, Natural Language Processing, H2O
Detection of Abnormal CAN Messages Using Periodicity and Time Series Analysis
Se-Rin Kim, Ji-Hyun Sung, Beom-Heon Youn, Harksu Cho The Transactions of the Korea Information Processing Society,
Vol. 13, No. 9, pp. 395-403,
Sep.
2024
https://doi.org/10.3745/TKIPS.2024.13.9.395
Keywords: CAN, GRU, Anomaly Detection, Time Series, Machine Learning

Keywords: CAN, GRU, Anomaly Detection, Time Series, Machine Learning
A Distinction Technology for Harmful Web Documents by Rates
Young Soo Kim , Taek Yong Nam , Dong Ho Won The KIPS Transactions:PartC,
Vol. 13, No. 7, pp. 859-864,
Dec.
2006
10.3745/KIPSTC.2006.13.7.859

Cox Model Improvement Using Residual Blocks in Neural Networks: A Study on the Predictive Model of Cervical Cancer Mortality
Nang Kyeong Lee, Joo Young Kim, Ji Soo Tak, Hyeong Rok Lee, Hyun Ji Jeon, Jee Myung Yang, Seung Won Lee The Transactions of the Korea Information Processing Society,
Vol. 13, No. 6, pp. 260-268,
Jun.
2024
https://doi.org/10.3745/TKIPS.2024.13.6.260
Keywords: Cervical cancer, Survival Prediction Model, Cox Proportional Hazards, Machine Learning, Deep Neural Networks, ResNet

Keywords: Cervical cancer, Survival Prediction Model, Cox Proportional Hazards, Machine Learning, Deep Neural Networks, ResNet
Evaluating the Efficiency of Models for Predicting Seismic Building Damage
Chae Song Hwa, Yujin Lim The Transactions of the Korea Information Processing Society,
Vol. 13, No. 5, pp. 217-220,
May.
2024
https://doi.org/10.3745/TKIPS.2024.13.5.217
Keywords: Earthquake, Earthquake Damage Prediction, Machine Learning(ml)

Keywords: Earthquake, Earthquake Damage Prediction, Machine Learning(ml)