Digital Library
Search: "[ keyword: Machine Learning ]" (74)
1D CNN and Machine Learning Methods for Fall Detection
Inkyung Kim, Daehee Kim, Song Noh, Jaekoo Lee KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 3, pp. 85-90,
Mar.
2021
https://doi.org/10.3745/KTSDE.2021.10.3.85
Keywords: Machine Learning, Deep Learning, Fall Detection, 1D Convolutional Neural Network
https://doi.org/10.3745/KTSDE.2021.10.3.85
Keywords: Machine Learning, Deep Learning, Fall Detection, 1D Convolutional Neural Network
Double Encoder-Decoder Model for Improving the Accuracy of the Electricity Consumption Prediction in Manufacturing
Yeongchang Cho, Byung Gill Go, Jong Hoon Sung, Yeong Sik Cho KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 12, pp. 419-430,
Dec.
2020
https://doi.org/10.3745/KTSDE.2020.9.12.419
Keywords: Time-Series Forecasting, Deep Learning, Machine Learning
https://doi.org/10.3745/KTSDE.2020.9.12.419
Keywords: Time-Series Forecasting, Deep Learning, Machine Learning
A Pre-processing Study to Solve the Problem of Rare Class Classification of Network Traffic Data
Ryu Kyung Joon, Shin DongIl, Shin DongKyoo, Park JeongChan, Kim JinGoog KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 12, pp. 411-418,
Dec.
2020
https://doi.org/10.3745/KTSDE.2020.9.12.411
Keywords: Machine Learning, Rare Class, Semi Rare Class, pre-processing, Feature selection
https://doi.org/10.3745/KTSDE.2020.9.12.411
Keywords: Machine Learning, Rare Class, Semi Rare Class, pre-processing, Feature selection
Analysis of Disaster Safety Situation Classification Algorithm Based on Natural Language Processing Using 119 Calls Data
Su-Jeong Kwon, Yun-Hee Kang, Yong-Hak Lee, Min-Ho Lee, Seung-Ho Park, Myung-Ju Kang KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 10, pp. 317-322,
Oct.
2020
https://doi.org/10.3745/KTSDE.2020.9.10.317
Keywords: Artificial intelligence, emergency response, Natural Language Processing, Situation Classification, Machine Learning
https://doi.org/10.3745/KTSDE.2020.9.10.317
Keywords: Artificial intelligence, emergency response, Natural Language Processing, Situation Classification, Machine Learning
Digital Mirror System with Machine Learning and Microservices
Myeong Ho Song, Soo Dong Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 9, pp. 267-280,
Sep.
2020
https://doi.org/10.3745/KTSDE.2020.9.9.267
Keywords: Digital Mirror, Face Recognition, Age Detection, Emotion Detection, Microservice, Machine Learning
https://doi.org/10.3745/KTSDE.2020.9.9.267
Keywords: Digital Mirror, Face Recognition, Age Detection, Emotion Detection, Microservice, Machine Learning
Tor Network Website Fingerprinting Using Statistical-Based Feature and Ensemble Learning of Traffic Data
Junho Kim, Wongyum Kim, Doosung Hwang KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 6, pp. 187-194,
Jun.
2020
https://doi.org/10.3745/KTSDE.2020.9.6.187
Keywords: Anonymous Network, Traffic Collection, Website Fingerprinting, Ensemble Algorithm, Machine Learning
https://doi.org/10.3745/KTSDE.2020.9.6.187
Keywords: Anonymous Network, Traffic Collection, Website Fingerprinting, Ensemble Algorithm, Machine Learning
Prediction of English Premier League Game Using an Ensemble Technique
Yi Jae Hyun, Lee Soo Won KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 5, pp. 161-168,
May.
2020
https://doi.org/10.3745/KTSDE.2020.9.5.161
Keywords: Machine Learning, Artificial intelligence, Sports Game Prediction, Ensemble Technique, Data Analysis
https://doi.org/10.3745/KTSDE.2020.9.5.161
Keywords: Machine Learning, Artificial intelligence, Sports Game Prediction, Ensemble Technique, Data Analysis
Hourly Prediction of Particulate Matter (PM2.5) Concentration Using Time Series Data and Random Forest
Deukwoo Lee, Soowon Lee KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 4, pp. 129-136,
Apr.
2020
https://doi.org/10.3745/KTSDE.2020.9.4.129
Keywords: Particulate Matter, PM2.5, Time Series Data, Machine Learning, Random Forest
https://doi.org/10.3745/KTSDE.2020.9.4.129
Keywords: Particulate Matter, PM2.5, Time Series Data, Machine Learning, Random Forest
Predicting Win-Loss of League of Legends Using Bidirectional LSTM Embedding
Cheolgi Kim, Soowon Lee KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 2, pp. 61-68,
Feb.
2020
https://doi.org/10.3745/KTSDE.2020.9.2.61
Keywords: League of Legends, Win-Loss Prediction, Machine Learning, Neural Network, LSTM
https://doi.org/10.3745/KTSDE.2020.9.2.61
Keywords: League of Legends, Win-Loss Prediction, Machine Learning, Neural Network, LSTM
Generating Training Dataset of Machine Learning Model for Context-Awareness in a Health Status Notification Service
Jong Hyeok Mun, Jong Sun Choi, Jae Young Choi KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 1, pp. 25-32,
Jan.
2020
https://doi.org/10.3745/KTSDE.2020.9.1.25
Keywords: context-awareness, Machine Learning Model, Generating Training Dataset, Maintaining Accuracy
https://doi.org/10.3745/KTSDE.2020.9.1.25
Keywords: context-awareness, Machine Learning Model, Generating Training Dataset, Maintaining Accuracy
Indexing
All publications of KTSDE is indexed in DOI, EBSCO, Google Scholar, Crossref, and CrossCheck.
KTSDE is also selected as the Journal for Accreditation by NRF (National Research Foundation of Korea).
