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Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: a review., , , , , , , and . Neural Comput. Appl., 35 (20): 14681-14722 (July 2023)Multilevel Weighted Feature Fusion Using Convolutional Neural Networks for EEG Motor Imagery Classification., , , , and . IEEE Access, (2019)Medical Image Forgery Detection for Smart Healthcare., , , and . IEEE Commun. Mag., 56 (4): 33-37 (2018)Smart-Edge-CoCaCo: AI-Enabled Smart Edge with Joint Computation, Caching, and Communication in Heterogeneous IoT., , , , , , and . CoRR, (2019)Smart-Edge-CoCaCo: AI-Enabled Smart Edge with Joint Computation, Caching, and Communication in Heterogeneous IoT., , , , , and . IEEE Netw., 33 (2): 58-64 (2019)Edge Intelligence in the Cognitive Internet of Things: Improving Sensitivity and Interactivity., , , , , and . IEEE Netw., 33 (3): 58-64 (2019)Electroencephalography-based motor imagery classification using temporal convolutional network fusion., , , , , , , , and . Biomed. Signal Process. Control., (2021)Deep Learning for EEG Motor Imagery-Based Cognitive Healthcare., , , , and . Connected Health in Smart Cities, Springer, (2020)Automated System for Colon Cancer Detection and Segmentation Based on Deep Learning Techniques., , , , , , , and . Int. J. Sociotechnology Knowl. Dev., 15 (1): 1-28 (2023)Cognitive Smart Healthcare for Pathology Detection and Monitoring., , , , and . IEEE Access, (2019)