Scientific Research Publishing

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ()

Graph Neural Networks for Anomaly Detection in Cloud Infrastructure ...
Scientific Research Publishing

Chen, H., Zhang, Y., Kalra, M.K., Lin, F., Chen, Y., Liao, P., et al. (2017) Low-Dose CT with a Residual Encoder-Decoder Convolutional Neural Network. IEEE Transactions on ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...
Frontiers

AM-MTEEG: multi-task EEG classification based on impulsive associative memory

Electroencephalogram-based brain-computer interfaces (BCIs) hold promise for healthcare applications but are hindered by cross-subject variability and limited data. This article proposes a multi-task ...
C&EN

EC2Vec: A Machine Learning Method to Embed Enzyme Commission (EC) Numbers into Vector Representations

Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, Louisiana 70803, United States Center for Computation and Technology, Louisiana State University, Baton Rouge, ...
Frontiers

MSGU-Net: a lightweight multi-scale ghost U-Net for image segmentation

U-Net and its variants have been widely used in the field of image segmentation. In this paper, a lightweight multi-scale Ghost U-Net (MSGU-Net) network architecture is proposed. This can efficiently ...
IEEE

Supervised Convolutional Encoder-Decoder With Gated Linear Units for Detecting Fetal R-Peaks

Abstract: Noninvasive fetal electrocardiography (ECG) is prevalently used for monitoring fetal heartbeats during pregnancy due to its affordability, ease of use, and constant monitoring capability. A ...
IEEE

NL-CoWNet: A Deep Convolutional Encoder–Decoder Architecture for OCT Speckle Elimination Using Nonlocal and Subband Modulated DT-CWT Blocks

Abstract: Optical coherence tomography (OCT), a noninvasive diagnostic technology for identifying and treating various ocular diseases, encounters a loss of image quality due to the introduction of ...
ahajournals.org

Evaluation of Diffusion Lesion Volume Measurements in Acute Ischemic Stroke Using Encoder-Decoder Convolutional Network

U-net, an encoder-decoder convolutional neural network, was adopted to train segmentation models. Two U-net models were developed: a U-net (DWI+ADC) model, trained on DWI and ADC data, and a U-net ...