| Sample-level Deep Convolutional Neural Networks for Music Auto-tagging Using Raw Waveforms J Lee, J Park, KL Kim, J Nam Proc. 14th Int. Conf. Sound and Music Computing Conference (SMC), 2017 | 216 | 2017 |
| SampleCNN: End-to-end deep convolutional neural networks using very small filters for music classification J Lee, J Park, KL Kim, J Nam Applied Sciences 8 (1), 150, 2018 | 165 | 2018 |
| Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-tagging J Lee, J Nam IEEE Signal Processing Letters 24 (8), 1208-1212, 2017 | 150 | 2017 |
| Deep learning for audio-based music classification and tagging: Teaching computers to distinguish rock from bach J Nam, K Choi, J Lee, SY Chou, YH Yang IEEE Signal Processing Magazine 36 (1), 41-51, 2018 | 109 | 2018 |
| Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms T Kim, J Lee, J Nam ICASSP, 2018 | 108 | 2018 |
| Comparison and analysis of SampleCNN architectures for audio classification T Kim, J Lee, J Nam IEEE Journal of Selected Topics in Signal Processing 13 (2), 285-297, 2019 | 89 | 2019 |
| Raw Waveform-based Audio Classification Using Sample-level CNN Architectures J Lee, T Kim, J Park, J Nam NeurIPS, Machine Learning for Audio Signal Processing Workshop (ML4Audio), 2017 | 86 | 2017 |
| Representation Learning of Music Using Artist Labels J Park, J Lee, J Park, JW Ha, J Nam ISMIR, 2018 | 68 | 2018 |
| Zero-shot learning for audio-based music classification and tagging J Choi, J Lee, J Park, J Nam ISMIR, 2019 | 47 | 2019 |
| Metric Learning vs Classification for Disentangled Music Representation Learning J Lee, NJ Bryan, J Salamon, Z Jin, J Nam ISMIR, 2020 | 37 | 2020 |
| Disentangled Multidimensional Metric Learning for Music Similarity J Lee, NJ Bryan, J Salamon, Z Jin, J Nam ICASSP, 2020 | 31 | 2020 |
| Combining Multi-scale Features Using Sample-level Deep Convolutional Neural Networks for Weakly Supervised Sound Event Detection J Lee, J Park, S Kum, Y Jeong, J Nam DCASE2017 Challenge/Workshop, 2017 | 19 | 2017 |
| Semantic tagging of singing voices in popular music recordings KL Kim, J Lee, S Kum, CL Park, J Nam IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 1656-1668, 2020 | 18 | 2020 |
| Deep content-user embedding model for music recommendation J Lee, K Lee, J Park, J Park, J Nam arXiv preprint arXiv:1807.06786, 2018 | 18 | 2018 |
| Multi-Level and Multi-Scale Feature Aggregation Using Sample-level Deep Convolutional Neural Networks for Music Classification J Lee, J Nam ICML, Machine Learning for Music Discovery Workshop, 2017 | 14 | 2017 |
| A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity S Park, T Kwon, J Lee, J Kim, J Nam ISMIR, 2019 | 12 | 2019 |
| Pseudo-Label Transfer From Frame-Level To Note-Level In A Teacher-Student Framework for Singing Transcription From Polyphonic Music S Kum, J Lee, KL Kim, T Kim, J Nam ICASSP, 2022 | 10 | 2022 |
| Representation Learning of Music Using Artist, Album, and Track Information J Lee, J Park, J Nam ICML, Machine Learning for Music Discovery Workshop, 2019 | 10 | 2019 |
| LP-MusicCaps: LLM-Based Pseudo Music Captioning SH Doh, K Choi, J Lee, J Nam ISMIR, 2023 | 8 | 2023 |
| Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging J Choi, J Lee, J Park, J Nam ICML, Machine Learning for Music Discovery Workshop, 2019 | 6 | 2019 |
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