From post

Examining Speaker and Keyword Uniqueness: Partitioning Keyword Spotting Datasets for Federated Learning with the Largest Differencing Method.

, , и . BNAIC/BENELEARN, том 1805 из Communications in Computer and Information Science, стр. 167-177. Springer, (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed.

 

Другие публикации лиц с тем же именем

How reliable are posterior class probabilities in automatic music classification?, , , , и . Audio Mostly Conference, стр. 45-50. ACM, (2023)Techniques Improving the Robustness of Deep Learning Models for Industrial Sound Analysis., и . EUSIPCO, стр. 81-85. IEEE, (2020)Exploring sound source separation for acoustic condition monitoring in industrial scenarios., , и . EUSIPCO, стр. 2264-2268. IEEE, (2017)Analyzing the Potential of Pre-Trained Embeddings for Audio Classification Tasks., , , и . EUSIPCO, стр. 790-794. IEEE, (2020)Ensemble Size Classification in Colombian Andean String Music Recordings., , , и . CMMR, том 12631 из Lecture Notes in Computer Science, стр. 60-74. Springer, (2019)DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection., , , , , , и . EUSIPCO, стр. 556-560. IEEE, (2021)Concept, implementation and evaluation of an improvisation based music video game., , и . ICE-GIC, стр. 210-212. IEEE, (2009)Uncertainty in Semi-Supervised Audio Classification - A Novel Extension for FixMatch., , , и . EUSIPCO, стр. 161-165. IEEE, (2023)Examining Speaker and Keyword Uniqueness: Partitioning Keyword Spotting Datasets for Federated Learning with the Largest Differencing Method., , и . BNAIC/BENELEARN, том 1805 из Communications in Computer and Information Science, стр. 167-177. Springer, (2022)Sounding Industry: Challenges and Datasets for Industrial Sound Analysis., , , и . EUSIPCO, стр. 1-5. IEEE, (2019)