| animal2vec and MeerKAT: A self-supervised transformer for rare-event raw audio input and a large-scale reference dataset for bioacoustics JC Schäfer-Zimmermann, V Demartsev, B Averly, K Dhanjal-Adams, ... arXiv preprint arXiv:2406.01253, 2024 | | 2024 |
| The past, present and future of underwater passive acoustic monitoring J Hildebrand, S Wiggins, S Baumann-Pickering, K Frasier, MA Roch The Journal of the Acoustical Society of America 155 (3_Supplement), A96-A96, 2024 | | 2024 |
| Navigating the bioacoustic landscape: Standardization and interoperability of acoustic data products MA Roch, S Baumann-Pickering, D Gillespie, J Kanes, K Kim, H Klinck, ... The Journal of the Acoustical Society of America 155 (3_Supplement), A95-A95, 2024 | | 2024 |
| Behavioral sequences across multiple animal species in the wild share common structural features P Minasandra, EM Grout, K Brock, MC Crofoot, V Demartsev, AS Gersick, ... bioRxiv, 2024.01. 20.576411, 2024 | | 2024 |
| Ecological inferences about marine mammals from passive acoustic data E Fleishman, D Cholewiak, D Gillespie, T Helble, H Klinck, EM Nosal, ... Biological Reviews 98 (5), 1633-1647, 2023 | 8 | 2023 |
| Signalling in groups: New tools for the integration of animal communication and collective movement V Demartsev, AS Gersick, FH Jensen, M Thomas, MA Roch, MB Manser, ... Methods in Ecology and Evolution 14 (8), 1852-1863, 2023 | 26 | 2023 |
| Using deep learning to track time× frequency whistle contours of toothed whales without human-annotated training data P Li, X Liu, H Klinck, P Gruden, MA Roch The Journal of the Acoustical Society of America 154 (1), 502-517, 2023 | 1 | 2023 |
| Learning stage-wise gans for whistle extraction in time-frequency spectrograms P Li, MA Roch, H Klinck, E Fleishman, D Gillespie, EM Nosal, Y Shiu, ... IEEE Transactions on Multimedia 25, 9302-9314, 2023 | 7 | 2023 |
| Silbido profundo: An open source package for the use of deep learning to detect odontocete whistles PC Conant, P Li, X Liu, H Klinck, E Fleishman, D Gillespie, EM Nosal, ... The Journal of the Acoustical Society of America 152 (6), 3800-3808, 2022 | 2 | 2022 |
| A practical guide for generating unsupervised, spectrogram‐based latent space representations of animal vocalizations M Thomas, FH Jensen, B Averly, V Demartsev, MB Manser, T Sainburg, ... Journal of Animal Ecology 91 (8), 1567-1581, 2022 | 26 | 2022 |
| Performance metrics for marine mammal signal detection and classification JA Hildebrand, KE Frasier, TA Helble, MA Roch The Journal of the Acoustical Society of America 151 (1), 414-427, 2022 | 18 | 2022 |
| Long-term patterns of noise from underwater explosions and their relation to fisheries in Southern California A Krumpel, A Rice, KE Frasier, F Reese, JS Trickey, AE Simonis, JP Ryan, ... Frontiers in Marine Science 8, 796849, 2021 | 2 | 2021 |
| Introduction to the special issue on machine learning in acoustics ZH Michalopoulou, P Gerstoft, B Kostek, MA Roch The Journal of the Acoustical Society of America 150 (4), 3204-3210, 2021 | 22 | 2021 |
| Improve automatic detection of animal call sequences with temporal context S Madhusudhana, Y Shiu, H Klinck, E Fleishman, X Liu, EM Nosal, ... Journal of the Royal Society Interface 18 (180), 20210297, 2021 | 32 | 2021 |
| Using context to train time-domain echolocation click detectors MA Roch, S Lindeneau, GS Aurora, KE Frasier, JA Hildebrand, H Glotin, ... The Journal of the Acoustical Society of America 149 (5), 3301-3310, 2021 | 15 | 2021 |
| How machine learning contributes to solve acoustical problems MA Roch, P Gerstoft, B Kostek, ZH Michalopoulou Journal of the Acoustical Society of America 17, 48-57, 2021 | 8 | 2021 |
| Temporal context improves automatic recognition of call sequences in soundscape data S Madhusudhana, Y Shiu, H Klinck, E Fleishman, X Liu, EM Nosal, ... The Journal of the Acoustical Society of America 148 (4_Supplement), 2442-2442, 2020 | 5 | 2020 |
| Learning deep models from synthetic data for extracting dolphin whistle contours P Li, X Liu, KJ Palmer, E Fleishman, D Gillespie, EM Nosal, Y Shiu, ... 2020 International Joint Conference on Neural Networks (IJCNN), 1-10, 2020 | 24 | 2020 |
| Deep neural networks for automated detection of marine mammal species Y Shiu, KJ Palmer, MA Roch, E Fleishman, X Liu, EM Nosal, T Helble, ... Scientific reports 10 (1), 607, 2020 | 166 | 2020 |
| Machine learning in acoustics: Theory and applications MJ Bianco, P Gerstoft, J Traer, E Ozanich, MA Roch, S Gannot, ... The Journal of the Acoustical Society of America 146 (5), 3590-3628, 2019 | 480 | 2019 |
John HildebrandProfessor of Oceanography, Scripps Institution of Oceanography, University of California San Diego在 ucsd.edu 的电子邮件经过验证
