AIMC Topic: Neural Networks, Computer

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The minimum regret path problem on stochastic fuzzy time-varying networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, we introduce a stochastic fuzzy time-varying minimum regret path problem (SFTMRP), which combines the characteristics of the min-max regret path and maximum probability path as a variant of the stochastic fuzzy time-varying shortest pa...

SIRe-Networks: Convolutional neural networks architectural extension for information preservation via skip/residual connections and interlaced auto-encoders.

Neural networks : the official journal of the International Neural Network Society
Improving existing neural network architectures can involve several design choices such as manipulating the loss functions, employing a diverse learning strategy, exploiting gradient evolution at training time, optimizing the network hyper-parameters...

Learning in deep neural networks and brains with similarity-weighted interleaved learning.

Proceedings of the National Academy of Sciences of the United States of America
Understanding how the brain learns throughout a lifetime remains a long-standing challenge. In artificial neural networks (ANNs), incorporating novel information too rapidly results in catastrophic interference, i.e., abrupt loss of previously acquir...

Pathological-Gait Recognition Using Spatiotemporal Graph Convolutional Networks and Attention Model.

Sensors (Basel, Switzerland)
Walking is an exercise that uses muscles and joints of the human body and is essential for understanding body condition. Analyzing body movements through gait has been studied and applied in human identification, sports science, and medicine. This st...

Semi-ProtoPNet Deep Neural Network for the Classification of Defective Power Grid Distribution Structures.

Sensors (Basel, Switzerland)
Power distribution grids are typically installed outdoors and are exposed to environmental conditions. When contamination accumulates in the structures of the network, there may be shutdowns caused by electrical arcs. To improve the reliability of th...

Prediction of Daily Ambient Temperature and Its Hourly Estimation Using Artificial Neural Networks in an Agrometeorological Station in Castile and León, Spain.

Sensors (Basel, Switzerland)
This study evaluates the predictive modeling of the daily ambient temperature (maximum, T; average, T; and minimum, T) and its hourly estimation (T, …, T) using artificial neural networks (ANNs) for agricultural applications. The data, 2004-2010, wer...

Fusion Poser: 3D Human Pose Estimation Using Sparse IMUs and Head Trackers in Real Time.

Sensors (Basel, Switzerland)
The motion capture method using sparse inertial sensors is an approach for solving the occlusion and economic problems in vision-based methods, which is suitable for virtual reality applications and works in complex environments. However, VR applicat...

SDNN-PPI: self-attention with deep neural network effect on protein-protein interaction prediction.

BMC genomics
BACKGROUND: Protein-protein interactions (PPIs) dominate intracellular molecules to perform a series of tasks such as transcriptional regulation, information transduction, and drug signalling. The traditional wet experiment method to obtain PPIs info...

A BERT-Based Aspect-Level Sentiment Analysis Algorithm for Cross-Domain Text.

Computational intelligence and neuroscience
Cross-domain text sentiment analysis is a text sentiment classification task that uses the existing source domain annotation data to assist the target domain, which can not only reduce the workload of new domain data annotation, but also significantl...

An Intelligent System for Detecting Abnormal Behavior in Students Based on the Human Skeleton and Deep Learning.

Computational intelligence and neuroscience
With the use of an intelligent video system, this research provides a method for detecting abnormal behavior based on the human skeleton and deep learning. To begin with, the spatiotemporal features of human bones are extracted through iterative trai...