| Anomalous sound detection based on interpolation deep neural network K Suefusa, T Nishida, H Purohit, R Tanabe, T Endo, Y Kawaguchi ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 136 | 2020 |
| Description and discussion on DCASE 2022 challenge task 2: Unsupervised anomalous sound detection for machine condition monitoring applying domain generalization techniques K Dohi, K Imoto, N Harada, D Niizumi, Y Koizumi, T Nishida, H Purohit, ... arXiv preprint arXiv:2206.05876, 2022 | 89 | 2022 |
| MIMII DG: Sound dataset for malfunctioning industrial machine investigation and inspection for domain generalization task K Dohi, T Nishida, H Purohit, R Tanabe, T Endo, M Yamamoto, Y Nikaido, ... arXiv preprint arXiv:2205.13879, 2022 | 86 | 2022 |
| Description and discussion on DCASE 2023 challenge task 2: First-shot unsupervised anomalous sound detection for machine condition monitoring K Dohi, K Imoto, N Harada, D Niizumi, Y Koizumi, T Nishida, H Purohit, ... arXiv preprint arXiv:2305.07828, 2023 | 33 | 2023 |
| MeshRIR: A dataset of room impulse responses on meshed grid points for evaluating sound field analysis and synthesis methods S Koyama, T Nishida, K Kimura, T Abe, N Ueno, J Brunnström 2021 IEEE Workshop on Applications of Signal Processing to Audio and …, 2021 | 28 | 2021 |
| Anomalous sound detection based on machine activity detection T Nishida, K Dohi, T Endo, M Yamamoto, Y Kawaguchi 2022 30th European Signal Processing Conference (EUSIPCO), 269-273, 2022 | 10 | 2022 |
| Region-restricted sensor placement based on Gaussian process for sound field estimation T Nishida, N Ueno, S Koyama, H Saruwatari IEEE Transactions on Signal Processing 70, 1718-1733, 2022 | 8 | 2022 |
| Mutual-information-based sensor placement for spatial sound field recording K Ariga, T Nishida, S Koyama, N Ueno, H Saruwatari ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 8 | 2020 |
| Fast semi-supervised anomaly detection of drivers’ behavior using online sequential extreme learning machine H Oikawa, T Nishida, R Sakamoto, H Matsutani, M Kondo 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 7 | 2020 |
| Sensor placement in arbitrarily restricted region for field estimation based on Gaussian process T Nishida, N Ueno, S Koyama, H Saruwatari 2020 28th European Signal Processing Conference (EUSIPCO), 2289-2293, 2021 | 4 | 2021 |
| Audio-change captioning to explain machine-sound anomalies STY Kawaguchi, T Nishida, K Imoto, Y Okamoto, K Dohi, T Endo Proceedings of the DCASE 2023 Workshop, 2023 | 1 | 2023 |
| Using ARCFACE Metric Learning For Low-Complexity Acoustic Scene Classification K Horváth, H Purohit, R Tanabe, K Dohi, T Endo, M Yamamoto, T Nishida, ... Detection and Classification of Acoustic Scenes and Events, 2021 | 1 | 2021 |
| The absolute configuration of cervicarcin; application of the aromatic chrality method S Marumo, N Harada, K Nakanishi, T Nishida Journal of the Chemical Society D: Chemical Communications, 1693-1694, 1970 | 1 | 1970 |
| Zero-shot domain adaptation of anomalous samples for semi-supervised anomaly detection T Nishida, T Endo, Y Kawaguchi ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
| Sensor placement allowing independent setting of estimation and candidate regions for field estimation based on Gaussian process T Nishida, N Ueno, S Koyama, H Saruwatari 電子情報通信学会技術研究報告 119 (440 (SIP2019 103-169)), 141-146, 2020 | | 2020 |
