1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CV2024
MaskMatch: Boosting Semi-Supervised Learning Through Mask Autoencoder-Driven Feature Learning
Wenjin Zhang, Keyi Li, Sen Yang +4
Conventional methods in semi-supervised learning (SSL) often face challenges related to limited data utilization, mainly due to their reliance on threshold-based techniques for sel…
eess.AS2024★ 1 cited
Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models
Chenyang Gao, Brecht Desplanques, Chelsea J. -T. Ju +2
Automated speaker identification (SID) is a crucial step for the personalization of a wide range of speech-enabled services. Typical SID systems use a symmetric enrollment-verifica…