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- research-articleOctober 2021
ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data
MM '21: Proceedings of the 29th ACM International Conference on MultimediaPages 3918–3926https://doi.org/10.1145/3474085.3475405Most of the current supervised automatic music transcription (AMT) models lack the ability to generalize. This means that they have trouble transcribing real-world music recordings from diverse musical genres that are not presented in the labelled ...
- research-articleMarch 2021
SelfHAR: Improving Human Activity Recognition through Self-training with Unlabeled Data
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Volume 5, Issue 1Article No.: 36, Pages 1–30https://doi.org/10.1145/3448112Machine learning and deep learning have shown great promise in mobile sensing applications, including Human Activity Recognition. However, the performance of such models in real-world settings largely depends on the availability of large datasets that ...