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Search: "[ keyword: LSTM ]" (10)
Comparison of Deep Learning Models Using Protein Sequence Data
Jeung Min Lee, Hyun Lee KIPS Transactions on Software and Data Engineering,
Vol. 11, No. 6, pp. 245-254,
Jun.
2022
https://doi.org/10.3745/KTSDE.2022.11.6.245
Keywords: CNN, LSTM, GRU, Combined Model, Protein Sequence

Keywords: CNN, LSTM, GRU, Combined Model, Protein Sequence
Understanding the Association Between Cryptocurrency Price Predictive Performance and Input Features
Jaehyun Park, Yeong-Seok Seo KIPS Transactions on Software and Data Engineering,
Vol. 11, No. 1, pp. 19-28,
Jan.
2022
https://doi.org/10.3745/KTSDE.2022.11.1.19
Keywords: LSTM, Deep Learning, Input Feature, Cryptocurrency, Price Prediction, Data Analysis

Keywords: LSTM, Deep Learning, Input Feature, Cryptocurrency, Price Prediction, Data Analysis
Fall Detection Based on 2-Stacked Bi-LSTM and Human-Skeleton Keypoints of RGBD Camera
Shin Byung Geun, Kim Uung Ho, Lee Sang Woo, Yang Jae Young, Kim Wongyum KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 11, pp. 491-500,
Nov.
2021
https://doi.org/10.3745/KTSDE.2021.10.11.491
Keywords: Fall Detection, deep-learning, Skeleton Keypoints, Stacked Bi-LSTM

Keywords: Fall Detection, deep-learning, Skeleton Keypoints, Stacked Bi-LSTM
Leased Line Traffic Prediction Using a Recurrent Deep Neural Network Model
In-Gyu Lee, Mi-Hwa Song KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 10, pp. 391-398,
Oct.
2021
https://doi.org/10.3745/KTSDE.2021.10.10.391
Keywords: Leased Line, Traffic Modeling, time series analysis, Deep Learning, RNN, LSTM

Keywords: Leased Line, Traffic Modeling, time series analysis, Deep Learning, RNN, LSTM
LSTM(Long Short-Term Memory)-Based AbnormalBehavior Recognition Using AlphaPose
Hyun-Jae Bae, Gyu-Jin Jang, Young-Hun Kim, Jin-Pyung Kim KIPS Transactions on Software and Data Engineering,
Vol. 10, No. 5, pp. 187-194,
May.
2021
https://doi.org/10.3745/KTSDE.2021.10.5.187
Keywords: Safety management, Action Recognition, Pose Estimation, LSTM, Deep Learning

Keywords: Safety management, Action Recognition, Pose Estimation, LSTM, Deep Learning
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

Keywords: League of Legends, Win-Loss Prediction, Machine Learning, Neural Network, LSTM
Topic Analysis of the National Petition Site and Prediction of Answerable Petitions Based on Deep Learning
Woo Yun Hui, Hyon Hee Kim KIPS Transactions on Software and Data Engineering,
Vol. 9, No. 2, pp. 45-52,
Feb.
2020
https://doi.org/10.3745/KTSDE.2020.9.2.45
Keywords: National Petition, Topic Analysis, topic modeling, K-Means Clustering, LSTM, Deep Learning

Keywords: National Petition, Topic Analysis, topic modeling, K-Means Clustering, LSTM, Deep Learning
Automatic Word Spacing of the Korean Sentences by Using End-to-End Deep Neural Network
Hyun Young Lee, Seung Shik Kang KIPS Transactions on Software and Data Engineering,
Vol. 8, No. 11, pp. 441-448,
Nov.
2019
https://doi.org/10.3745/KTSDE.2019.8.11.441
Keywords: Syllable Embedding, Bi-LSTM, Feedforward Neural Network, Neural Network Language Model, Linear-Chain CRF

Keywords: Syllable Embedding, Bi-LSTM, Feedforward Neural Network, Neural Network Language Model, Linear-Chain CRF
An LSTM Method for Natural Pronunciation Expression of Foreign Words in Sentences
Sungdon Kim, Jaehee Jung KIPS Transactions on Software and Data Engineering,
Vol. 8, No. 4, pp. 163-170,
Apr.
2019
https://doi.org/10.3745/KTSDE.2019.8.4.163
Keywords: Postposition, LSTM, Dropout, Overfitting, Final Consonant Pronunciation of Nouns

Keywords: Postposition, LSTM, Dropout, Overfitting, Final Consonant Pronunciation of Nouns
Indoor Air Condition Measurement and Regression Analysis System Through Sensor Measurement Device and Gated Recurrent Unit
Jaehyun Ahn, Dongil Shin, Kyuho Kim, Jihoon Yang KIPS Transactions on Software and Data Engineering,
Vol. 6, No. 9, pp. 457-464,
Sep.
2017
10.3745/KTSDE.2017.6.9.457
Keywords: Atmospheric Observation System, Time Series Prediction, Long-Short Term Memory(LSTM), Circuit Type Circulation Unit(GRU)

Keywords: Atmospheric Observation System, Time Series Prediction, Long-Short Term Memory(LSTM), Circuit Type Circulation Unit(GRU)