AIMC Topic: Neural Networks, Computer

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Extending the Morphological Hit-or-Miss Transform to Deep Neural Networks.

IEEE transactions on neural networks and learning systems
While most deep learning architectures are built on convolution, alternative foundations such as morphology are being explored for purposes such as interpretability and its connection to the analysis and processing of geometric structures. The morpho...

A Bilevel Learning Model and Algorithm for Self-Organizing Feed-Forward Neural Networks for Pattern Classification.

IEEE transactions on neural networks and learning systems
Conventional artificial neural network (ANN) learning algorithms for classification tasks, either derivative-based optimization algorithms or derivative-free optimization algorithms work by training ANN first (or training and validating ANN) and then...

Discrete-Time H Neural Control Using Reinforcement Learning.

IEEE transactions on neural networks and learning systems
In this article, we discuss H control for unknown nonlinear systems in discrete time. A discrete-time recurrent neural network is used to model the nonlinear system, and then, the H tracking control is applied based on the neural model. Since this ne...

Self-Attention-Based Models for the Extraction of Molecular Interactions from Biological Texts.

Biomolecules
For any molecule, network, or process of interest, keeping up with new publications on these is becoming increasingly difficult. For many cellular processes, the amount molecules and their interactions that need to be considered can be very large. Au...

Feasibility of a Neural Network-Based Virtual Sensor for Vehicle Unsprung Mass Relative Velocity Estimation.

Sensors (Basel, Switzerland)
With the automotive industry moving towards automated driving, sensing is increasingly important in enabling technology. The virtual sensors allow data fusion from various vehicle sensors and provide a prediction for measurement that is hard or too e...

SEFPN: Scale-Equalizing Feature Pyramid Network for Object Detection.

Sensors (Basel, Switzerland)
Feature Pyramid Network (FPN) is used as the neck of current popular object detection networks. Research has shown that the structure of FPN has some defects. In addition to the loss of information caused by the reduction of the channel number, the f...

Energy Load Forecasting Using a Dual-Stage Attention-Based Recurrent Neural Network.

Sensors (Basel, Switzerland)
Providing a stable, low-price, and safe supply of energy to end-users is a challenging task. The energy service providers are affected by several events such as weather, volatility, and special events. As such, the prediction of these events and havi...

A Graph Feature Auto-Encoder for the prediction of unobserved node features on biological networks.

BMC bioinformatics
BACKGROUND: Molecular interaction networks summarize complex biological processes as graphs, whose structure is informative of biological function at multiple scales. Simultaneously, omics technologies measure the variation or activity of genes, prot...

Analysis of Cardiac Ultrasound Images of Critically Ill Patients Using Deep Learning.

Journal of healthcare engineering
Cardiovascular disease remains a substantial cause of morbidity and mortality in the developed world and is becoming an increasingly important cause of death in developing countries too. While current cardiovascular treatments can assist to reduce th...

Study on 3D Image Reconstruction Model of Sparring Action Based on Graph Neural Network (GNN).

Computational intelligence and neuroscience
With the advent of the information age, human demand for information is increasing day by day. The emergence of the concept of big data has triggered a new round of technological revolution, and visual information plays an important role in informati...