AIMC Topic: Neural Networks, Computer

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Automation of Cephalometrics Using Machine Learning Methods.

Computational intelligence and neuroscience
Cephalometry is a medical test that can detect teeth, skeleton, or appearance problems. In this scenario, the patient's lateral radiograph of the face was utilised to construct a tracing from the tracing of lines on the lateral radiograph of the face...

Feature Extraction of Athlete's Post-Match Psychological and Emotional Changes Based on Deep Learning.

Computational intelligence and neuroscience
Athletes have had to deal with significant shifts in the way they think about psychology and emotion before and after attending a match in their respective fields. It has become increasingly difficult for players of any sport to overcome these differ...

Network Security Situation Prediction Model Based on EMD and ELPSO Optimized BiGRU Neural Network.

Computational intelligence and neuroscience
In order to improve the accuracy of network security situation prediction and the convergence speed of prediction algorithm, this paper proposes a combined prediction model (EMD-ELPSO-BiGRU) based on empirical mode decomposition (EMD) and improved pa...

GFINNs: GENERIC formalism informed neural networks for deterministic and stochastic dynamical systems.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We propose the GENERIC formalism informed neural networks (GFINNs) that obey the symmetric degeneracy conditions of the GENERIC formalism. GFINNs comprise two modules, each of which contains two components. We model each component using a neural netw...

Machine learning-based statistical closure models for turbulent dynamical systems.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
We propose a machine learning (ML) non-Markovian closure modelling framework for accurate predictions of statistical responses of turbulent dynamical systems subjected to external forcings. One of the difficulties in this statistical closure problem ...

DeepRF: A deep learning method for predicting metabolic pathways in organisms based on annotated genomes.

Computers in biology and medicine
The rapid increase of metabolomics has led to an increasing focus on metabolic pathway modeling and reconstruction. In particular, reconstructing an organism's metabolic network based on its genome sequence is a key challenge in systems biology. The ...

Codimension-2 parameter space structure of continuous-time recurrent neural networks.

Biological cybernetics
If we are ever to move beyond the study of isolated special cases in theoretical neuroscience, we need to develop more general theories of neural circuits over a given neural model. The present paper considers this challenge in the context of continu...

Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder.

Sensors (Basel, Switzerland)
As an essential task in computer vision, video anomaly detection technology is used in video surveillance, scene understanding, road traffic analysis and other fields. However, the definition of anomaly, scene change and complex background present gr...