Titlebook: Mathematical Analysis and the Mathematics of Computation; Werner Römisch,Thomas Zeugmann Textbook 2016 Springer International Publishing S

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putational burdens, improve classification performance and enhance model interpretability, in multi-label learning. Mutual information (MI) between two random variables is widely used to describe feature-label relevance and feature-feature redundancy. Furthermore, multivariate mutual information (MM

奴才

Werner Römisch,Thomas Zeugmannand personalized gait trajectories designed for robot assisted gait training are very important for improving the therapeutic results. Meanwhile, it has been proved that human gaits are closely related to anthropometric features, which however has not been well researched. Therefore, a method based

青少年

Werner Römisch,Thomas Zeugmannand personalized gait trajectories designed for robot assisted gait training are very important for improving the therapeutic results. Meanwhile, it has been proved that human gaits are closely related to anthropometric features, which however has not been well researched. Therefore, a method based

Diverticulitis

Werner Römisch,Thomas Zeugmann application range is greatly restricted by the specialized task (i.e., a specific model is required for each considered noise level), which prompts us to train a single network to tackle the blind image denoising problem. To this end, we take the advantages of state-of-the-art progress in deep lear

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Werner Römisch,Thomas Zeugmannthis paper, we propose a novel image-based malware classification model using deep learning to counter large-scale malware analysis. The model includes a malware embedding method called YongImage which maps instruction-level information and disassembly metadata generated by IDA disassembler tool int