Baekcheol Jang

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1 Similar Profiles

59 Article
7 Conference contribution
2 Review article

Long-Term Influenza Outbreak Forecast Using Time-Precedence Correlation of Web Data
Jang, B., Kim, I. & Kim, J. W., 2023 May 1, In: IEEE Transactions on Neural Networks and Learning Systems. 34, 5, p. 2400-2412 13 p.
Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus)
Survey of Landmark-based Indoor Positioning Technologies
Jang, B., Kim, H. & Kim, J. W., 2023 Jan, In: Information Fusion. 89, p. 166-188 23 p.
Research output: Contribution to journal › Article › peer-review

Open Access
1 Citation (Scopus)
Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data
Chung, J. & Jang, B., 2022 Nov, In: PloS one. 17, 11 November, e0278071.
Research output: Contribution to journal › Article › peer-review

Open Access
A Multi-Headed Transformer Approach for Predicting the Patient's Clinical Time-Series Variables From Charted Vital Signs
Harerimana, G., Kim, J. W. & Jang, B., 2022, In: IEEE Access. 10, p. 105993-106004 12 p.
Research output: Contribution to journal › Article › peer-review

Open Access
Deep learning-based privacy-preserving framework for synthetic trajectory generation
Kim, J. W. & Jang, B., 2022 Oct, In: Journal of Network and Computer Applications. 206, 103459.
Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus)

Researchers at Yonsei University Target Mathematics (Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection)
Baekcheol Jang
23/2/24
1 item of Media coverage
Press/Media: Press / Media
Study Results from Yonsei University Broaden Understanding of Technology (Survey of Landmark-based Indoor Positioning Technologies)
Baekcheol Jang
22/12/29
1 item of Media coverage
Press/Media: Press / Media

Baekcheol Jang

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Research output

Long-Term Influenza Outbreak Forecast Using Time-Precedence Correlation of Web Data

Survey of Landmark-based Indoor Positioning Technologies

Accurate prediction of electricity consumption using a hybrid CNN-LSTM model based on multivariable data

A Multi-Headed Transformer Approach for Predicting the Patient's Clinical Time-Series Variables From Charted Vital Signs

Deep learning-based privacy-preserving framework for synthetic trajectory generation

Press/Media

Researchers at Yonsei University Target Mathematics (Petroleum Price Prediction with CNN-LSTM and CNN-GRU Using Skip-Connection)

Study Results from Yonsei University Broaden Understanding of Technology (Survey of Landmark-based Indoor Positioning Technologies)