AIMC Topic: Neural Networks, Computer

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Neural interface systems with on-device computing: machine learning and neuromorphic architectures.

Current opinion in biotechnology
Development of neural interface and brain-machine interface (BMI) systems enables the treatment of neurological disorders including cognitive, sensory, and motor dysfunctions. While neural interfaces have steadily decreased in form factor, recent dev...

A Comparative Study of Marginalized Graph Kernel and Message-Passing Neural Network.

Journal of chemical information and modeling
This work proposes a state-of-the-art hybrid kernel to calculate molecular similarity. Combined with Gaussian process models, the performance of the hybrid kernel in predicting molecular properties is comparable to that of the directed message-passin...

Stochastic Spiking Behavior in Neuromorphic Networks Enables True Random Number Generation.

ACS applied materials & interfaces
There is currently a great deal of interest in the use of nanoscale devices to emulate the behaviors of neurons and synapses and to facilitate brain-inspired computation. Here, it is shown that percolating networks of nanoparticles exhibit stochastic...

A Fast Intrusion Detection Method for High-Speed Railway Clearance Based on Low-Cost Embedded GPUs.

Sensors (Basel, Switzerland)
The efficiency and the effectiveness of railway intrusion detection are crucial to the safety of railway transportation. Most current methods of railway intrusion detection or obstacle detection are inappropriate for large-scale applications due to t...

Estimating the COVID-19 prevalence and mortality using a novel data-driven hybrid model based on ensemble empirical mode decomposition.

Scientific reports
In this study, we proposed a new data-driven hybrid technique by integrating an ensemble empirical mode decomposition (EEMD), an autoregressive integrated moving average (ARIMA), with a nonlinear autoregressive artificial neural network (NARANN), cal...

A neural network for glomerulus classification based on histological images of kidney biopsy.

BMC medical informatics and decision making
BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results....

Interpretable Diagnosis for Whole-Slide Melanoma Histology Images Using Convolutional Neural Network.

Journal of healthcare engineering
At present, deep learning-based medical image diagnosis had achieved high performance in several diseases. However, the black-box nature of the convolutional neural network (CNN) limits their role in diagnosis. In this study, a novel interpretable di...

Improved Protein Structure Prediction Using a New Multi-Scale Network and Homologous Templates.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
The accuracy of de novo protein structure prediction has been improved considerably in recent years, mostly due to the introduction of deep learning techniques. In this work, trRosettaX, an improved version of trRosetta for protein structure predicti...

A nested parallel multiscale convolution for cerebrovascular segmentation.

Medical physics
PURPOSE: Cerebrovascular segmentation in magnetic resonance imaging (MRI) plays an important role in the diagnosis and treatment of cerebrovascular diseases. Many segmentation frameworks based on convolutional neural networks (CNNs) or U-Net-like str...

Coastal Waste Detection Based on Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Coastal waste not only has a seriously destructive effect on human life and marine ecosystems, but it also poses a long-term economic and environmental threat. To solve the issues of a poor manual coastal waste sorting environment, such as low sortin...