Ensemble of Convolutional Neural Networks for Weakly-supervised Sound Event Detection Using Multiple Scale Input. D Lee, S Lee, Y Han, K Lee DCASE 1, 14-18, 2017 | 87 | 2017 |
Neural audio fingerprint for high-specific audio retrieval based on contrastive learning S Chang, D Lee, J Park, H Lim, K Lee, K Ko, Y Han ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 40 | 2021 |
Exploiting temporal and nonstationary features in breathing sound analysis for multiple obstructive sleep apnea severity classification J Kim, T Kim, D Lee, JW Kim, K Lee Biomedical engineering online 16, 1-18, 2017 | 22 | 2017 |
Development of an embedded molecular structure-based model for prediction of micropollutant treatability in a drinking water treatment plant by machine learning from three … JK Kang, D Lee, KE Muambo, J Choi, JE Oh Water Research 239, 120037, 2023 | 10 | 2023 |
Enhancing music features by knowledge transfer from user-item log data D Lee, J Lee, J Park, K Lee ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 9 | 2019 |
Cross-domain semi-supervised audio event classification using contrastive regularization D Lee, K Lee 2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021 | 3 | 2021 |
Room adaptive conditioning method for sound event classification in reverberant environments J Lee, D Lee, HS Choi, K Lee ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 2 | 2021 |
Covernet: Cover Song Identification Using Cross-Similarity Matrix With Convolutional Neural Network J Lee, S Chang, D Lee, K Lee | 2 | 2019 |