AIMC Topic: Neural Networks, Computer

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AR3D: Attention Residual 3D Network for Human Action Recognition.

Sensors (Basel, Switzerland)
At present, in the field of video-based human action recognition, deep neural networks are mainly divided into two branches: the 2D convolutional neural network (CNN) and 3D CNN. However, 2D CNN's temporal and spatial feature extraction processes are...

Smoothing inertial neurodynamic approach for sparse signal reconstruction via L-norm minimization.

Neural networks : the official journal of the International Neural Network Society
In this paper, we propose a smoothing inertial neurodynamic approach (SINA) which is used to deal with L-norm minimization problem to reconstruct sparse signals. Note that the considered optimization problem is nonsmooth, nonconvex and non-Lipschitz....

Knowledge graph embedding with shared latent semantic units.

Neural networks : the official journal of the International Neural Network Society
Knowledge graph embedding (KGE) aims to project both entities and relations into a continuous low-dimensional space. However, for a given knowledge graph (KG), only a small number of entities and relations occur many times, while the vast majority of...

Design of experiment (DOE) applied to artificial neural network architecture enables rapid bioprocess improvement.

Bioprocess and biosystems engineering
Modern bioprocess development employs statistically optimized design of experiments (DOE) and regression modeling to find optimal bioprocess set points. Using modeling software, such as JMP Pro, it is possible to leverage artificial neural networks (...

Semi-supervised GAN-based Radiomics Model for Data Augmentation in Breast Ultrasound Mass Classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The capability of deep learning radiomics (DLR) to extract high-level medical imaging features has promoted the use of computer-aided diagnosis of breast mass detected on ultrasound. Recently, generative adversarial network ...

External validation of automated focal cortical dysplasia detection using morphometric analysis.

Epilepsia
OBJECTIVE: Focal cortical dysplasias (FCDs) are a common cause of drug-resistant focal epilepsy but frequently remain undetected by conventional magnetic resonance imaging (MRI) assessment. The visual detection can be facilitated by morphometric anal...

A Machine Learning Approach as a Surrogate for a Finite Element Analysis: Status of Research and Application to One Dimensional Systems.

Sensors (Basel, Switzerland)
Current maintenance intervals of mechanical systems are scheduled a priori based on the life of the system, resulting in expensive maintenance scheduling, and often undermining the safety of passengers. Going forward, the actual usage of a vehicle wi...

Automated segmentation of the individual branches of the carotid arteries in contrast-enhanced MR angiography using DeepMedic.

BMC medical imaging
BACKGROUND: Non-invasive imaging is of interest for tracking the progression of atherosclerosis in the carotid bifurcation, and segmenting this region into its constituent branch arteries is necessary for analyses. The purpose of this study was to va...

miTAR: a hybrid deep learning-based approach for predicting miRNA targets.

BMC bioinformatics
BACKGROUND: microRNAs (miRNAs) have been shown to play essential roles in a wide range of biological processes. Many computational methods have been developed to identify targets of miRNAs. However, the majority of these methods depend on pre-defined...

Parallel Binary Image Cryptosystem Via Spiking Neural Networks Variants.

International journal of neural systems
Due to the inefficiency of multiple binary images encryption, a parallel binary image encryption framework based on the typical variants of spiking neural networks, spiking neural P (SNP) systems is proposed in this paper. More specifically, the two ...