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  • GitHub - jinxyBJTU GRM4WFER_2024
    Get Dataset; Access the dataset through the above links The dataset includes physiological signals and corresponding annotations Preprocessing; After downloading the dataset, preprocess the data according to its original instruction
  • Releases · jinxyBJTU GRM4WFER_2024 - GitHub
    Contribute to jinxyBJTU GRM4WFER_2024 development by creating an account on GitHub
  • Activity · jinxyBJTU GRM4WFER_2024 - GitHub
    Contribute to jinxyBJTU GRM4WFER_2024 development by creating an account on GitHub
  • Issues · jinxyBJTU GRM4WFER_2024 - GitHub
    Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community Issues are used to track todos, bugs, feature requests, and more As issues are created, they’ll appear here in a searchable and filterable list To get started
  • Group-wise relation mining for weakly-supervised fine-grained . . .
    The weakly-supervised paradigms (Dinkel et al , 2020, Du et al , 2021, Zhang et al , 2022) leverage minimal knowledge (e g , trial-wise coarse-grained labels) about the core events in training, which can be effortlessly obtained, facilitating fine-grained recognition in the inference stage This motivates us to explore the potential of weakly-supervised fine-grained emotion recognition (WFER





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