Recently, a research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, has developed a new deep learning method that improves the classification accuracy of mixed ...
Abstract: This study applies Bayesian learning techniques, specifically Variational Inference (VI) and Monte Carlo Dropout (MC Dropout) to Automatic Modulation Classification (AMC). Both methods are ...
Abstract: The efficient deployment of Big Data processing tasks in cloud environments is the basic core function of Big Data processing, which refers to the effective deployment of tasks to the ...
In Table 3, the VIF values for each variable are < 5, which has been reduced as multicollinearity between variables. 3.3. Use the Entropy Weight Method to Weight the Data When exploring the factors ...
Introduction: Motor imagery functional near-infrared spectroscopy (MI-fNIRS) offers precise monitoring of neural activity in stroke rehabilitation, yet accurate cross-subject classification remains ...
Introduction: Ovarian Cancer (OC) is one of the leading causes of cancer deaths among women. Despite recent advances in the medical field, such as surgery, chemotherapy, and radiotherapy interventions ...
In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...
1 Department of Computer Science, Rutgers University, New Brunswick, NJ, USA. 2 Department of Computer Science, Rochester Institute of Technology, Rochester, NY, USA. This paper presents a ...
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