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cs.LG2025
FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation
Pingyi Fan, Anbai Jiang, Shuwei Zhang +9
Industrial signal analysis is hindered by severe data heterogeneity, which we characterize as the M5 problem. Existing solutions rely on specialized models that lack robustness and…
cs.LG2024
MER 2024: Semi-Supervised Learning, Noise Robustness, and Open-Vocabulary Multimodal Emotion Recognition
Zheng Lian, Haiyang Sun, Licai Sun +15
Multimodal emotion recognition is an important research topic in artificial intelligence. Over the past few decades, researchers have made remarkable progress by increasing the dat…