Description
BCI MI signal Classification Framework using Fuzzy integrals.
Paper: Ko, L. W., Lu, Y. C., Bustince, H., Chang, Y. C., Chang, Y., Ferandez, J., ... & Lin, C. T. (2019). Multimodal fuzzy fusion for enhancing the motor-imagery-based brain computer interface. IEEE Computational Intelligence Magazine, 14(1), 96-106.
Papers Using This Method
Consistency-aware Fake Videos Detection on Short Video Platforms2025-04-30Multi-Layer Feature Fusion with Cross-Channel Attention-Based U-Net for Kidney Tumor Segmentation2024-10-20Training-Free Point Cloud Recognition Based on Geometric and Semantic Information Fusion2024-09-07MFF-EINV2: Multi-scale Feature Fusion across Spectral-Spatial-Temporal Domains for Sound Event Localization and Detection2024-06-13Trustworthy Sensor Fusion against Inaudible Command Attacks in Advanced Driver-Assistance System2023-05-30Semantic Feature Integration network for Fine-grained Visual Classification2023-02-13Transformer-based Context Condensation for Boosting Feature Pyramids in Object Detection2022-07-14Construction Cost Index Forecasting: A Multi-feature Fusion Approach2021-08-18ECG Heartbeat Classification Using Multimodal Fusion2021-07-21Small-Angle X-Ray Scattering Signatures of Conformational Heterogeneity and Homogeneity of Disordered Protein Ensembles2021-05-27Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions2021-01-18Towards Reducing Severe Defocus Spread Effects for Multi-Focus Image Fusion via an Optimization Based Strategy2020-12-29Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface2020-11-19MFFW: A new dataset for multi-focus image fusion2020-02-12Choquet integral in decision analysis - lessons from the axiomatization2016-11-29