Source: Yoshitaka Tomiyama Published: 2020-03-04 / 44 minutes / 24,000 views Scope: The second in a series of explanations ...
Unsafe-behavior recognition in factory production lines remains challenging because complex backgrounds, frequent occlusion, and strict real-time requirements often degrade detection accuracy and ...
The explosive growth in computation and energy cost of artificial intelligence has spurred interest in alternative computing modalities to conventional electronic processors. Photonic processors, ...
Spinal cord injury (SCI) may lead to impaired motor function, autonomic nervous system dysfunction, and other dysfunctions. Brain-computer Interface (BCI) system based on motor imagery (MI) can ...
In this study, we proposed a multiscale convolutional neural network (MsCNN) that can screen the Raman spectra of the hepatitis B (HB) serum rapidly without baseline correction. First, the Raman ...
The electroencephalography (EEG) is a well-established non-invasive method in neuroscientific research and clinical diagnostics. It provides a high temporal but low spatial resolution of brain ...
Boltzmann Generators, a machine learning method, generate equilibrium samples of molecular systems by learning a transformation from a simple prior distribution to the target Boltzmann distribution ...
Abstract: Graph classification is a fundamental but challenging issue for numerous real-world applications. Despite recent great progress in image/video classification, convolutional neural networks ...
Accurate inference of gene interactions and causality is required for pathway reconstruction, which remains a major goal for many studies. Here, we take advantage of 2 recent technological ...
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