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      Explainable diagnosis of secondary pulmonary tuberculosis by graph rank-based average pooling neural network

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          Learning Deep Features for Discriminative Localization

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            Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization

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              Covid-19 Classification by FGCNet with Deep Feature Fusion from Graph Convolutional Network and Convolutional Neural Network

              Highlights • We analysed over 320 COVID-19 images and 320 healthy control images. • We proposed an improved CNN to extract individual image-level features. • We proposed to use GCN to extract relation-aware representations. • We proposed a DFF technology to combine features from GCN and CNN. • The proposed FCGNet gives better performance than 15 state-of-the-art approaches.
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                Author and article information

                Journal
                Journal of Ambient Intelligence and Humanized Computing
                J Ambient Intell Human Comput
                Springer Science and Business Media LLC
                1868-5137
                1868-5145
                March 13 2021
                Article
                10.1007/s12652-021-02998-0
                364099c2-e177-4fec-9a80-de93bf62133e
                © 2021

                http://www.springer.com/tdm

                http://www.springer.com/tdm

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