| Deep convolutional neural networks for predominant instrument recognition in polyphonic music Y Han, J Kim, K Lee IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (1), 208-221, 2016 | 290 | 2016 |
| Make some noise: Unleashing the power of convolutional neural networks for profiled side-channel analysis JH Kim, S Picek, A Heuser, S Bhasin, A Hanjalic IACR Transactions on Cryptographic Hardware and Embedded Systems 2019 (3 …, 2019 | 284 | 2019 |
| On the performance of convolutional neural networks for side-channel analysis S Picek, IP Samiotis, J Kim, A Heuser, S Bhasin, A Legay Security, Privacy, and Applied Cryptography Engineering: 8th International …, 2018 | 126 | 2018 |
| One deep music representation to rule them all? A comparative analysis of different representation learning strategies J Kim, J Urbano, CCS Liem, A Hanjalic Neural Computing and Applications 32 (4), 1067-1093, 2020 | 68 | 2020 |
| Generative autoregressive networks for 3d dancing move synthesis from music H Ahn, J Kim, K Kim, S Oh IEEE Robotics and Automation Letters 5 (2), 3501-3508, 2020 | 48 | 2020 |
| Transfer learning of artist group factors to musical genre classification J Kim, M Won, X Serra, CCS Liem Companion Proceedings of the The Web Conference 2018, 1929-1934, 2018 | 25 | 2018 |
| Empirical study on ensemble method of deep neural networks for acoustic scene classification J Kim, K Lee Proc. of IEEE AASP Challenge on Detection and Classification of Acoustic …, 2016 | 20 | 2016 |
| Effects of auditory feedback on menu selection in hand-gesture interfaces Y Park, J Kim, K Lee IEEE MultiMedia 22 (1), 32-40, 2015 | 16 | 2015 |
| Towards seed-free music playlist generation: Enhancing collaborative filtering with playlist title information J Kim, M Won, CCS Liem, A Hanjalic Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018 | 14 | 2018 |
| Are Nearby Neighbors Relatives?: Testing Deep Music Embeddings J Kim, J Urbano, C Liem, A Hanjalic Frontiers in Applied Mathematics and Statistics 5, 53, 2019 | 10 | 2019 |
| Butter Lyrics Over Hominy Grit: Comparing Audio and Psychology-Based Text Features in MIR Tasks. J Kim, AM Demetriou, S Manolios, MS Tavella, CCS Liem ISMIR, 861-868, 2020 | 7 | 2020 |
| On the effect of data-augmentation on local embedding properties in the contrastive learning of music audio representations MC McCallum, MEP Davies, F Henkel, J Kim, SE Sandberg ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 4 | 2024 |
| Similar but faster: manipulation of tempo in music audio embeddings for tempo prediction and search MC McCallum, F Henkel, J Kim, SE Sandberg, MEP Davies ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 2 | 2024 |
| Contrastive learning for cross-modal artist retrieval A Ferraro, J Kim, S Oramas, A Ehmann, F Gouyon arXiv preprint arXiv:2308.06556, 2023 | 2 | 2023 |
| Tempo estimation as fully self-supervised binary classification F Henkel, J Kim, MC McCallum, SE Sandberg, MEP Davies ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | | 2024 |
| TOWARDS AUTOMATED ESTIMATION OF VALUES FROM SONG LYRICS: A DATA COLLECTION PROTOCOL AM Demetriou, J Kim, S Manolios, CCS Liem OSF Preprints, 2023 | | 2023 |
| The power of deep without going deep? A study of HDPGMM music representation learning J Kim, CCS Liem 23rd International Society for Music Information Retrieval Conference, 116-124, 2022 | | 2022 |
| Beyond Explicit Reports: Comparing Data-Driven Approaches to Studying Underlying Dimensions of Music Preference J Kim, AM Demetriou, S Manolios, CCS Liem Proceedings of the 27th ACM Conference on User Modeling, Adaptation and …, 2019 | | 2019 |
| Single and Multi Column Neural Networks for Content-based Music Genre Recognition. CW Kim, J Kim, K Kim, M Won MediaEval, 2017 | | 2017 |
| 음악 연주를 위한 비-태깅 기반 테이블탑 TUI (Tangible User Interface) 김재훈， 원상희， 이교구 한국 HCI 학회 학술대회, 925-928, 2014 | | 2014 |
Alan HanjalicProfessor of Computer Science, IEEE Fellow, Delft University of Technology, The NetherlandsBestätigte E-Mail-Adresse bei tudelft.nl
