AIMC Topic: Neural Networks, Computer

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Implementation of an Intelligent Exam Supervision System Using Deep Learning Algorithms.

Sensors (Basel, Switzerland)
Examination cheating activities like whispering, head movements, hand movements, or hand contact are extensively involved, and the rectitude and worthiness of fair and unbiased examination are prohibited by such cheating activities. The aim of this r...

ResSUMO: A Deep Learning Architecture Based on Residual Structure for Prediction of Lysine SUMOylation Sites.

Cells
Lysine SUMOylation plays an essential role in various biological functions. Several approaches integrating various algorithms have been developed for predicting SUMOylation sites based on a limited dataset. Recently, the number of identified SUMOylat...

Lightweight convolutional neural network for aircraft small target real-time detection in Airport videos in complex scenes.

Scientific reports
Airport aircraft identification has essential application value in conflict early warning, anti-runway foreign body intrusion, remote command, etc. The scene video images have problems such as small aircraft targets and mutual occlusion due to the ex...

Haplotype and population structure inference using neural networks in whole-genome sequencing data.

Genome research
Accurate inference of population structure is important in many studies of population genetics. Here we present HaploNet, a method for performing dimensionality reduction and clustering of genetic data. The method is based on local clustering of phas...

A Frobenius Norm Regularization Method for Convolutional Kernel Tensors in Neural Networks.

Computational intelligence and neuroscience
The convolutional neural network is a very important model of deep learning. It can help avoid the exploding/vanishing gradient problem and improve the generalizability of a neural network if the singular values of the Jacobian of a layer are bounded...

Comparative studies of deep learning segmentation models for left ventricle segmentation.

Frontiers in public health
One of the primary factors contributing to death across all age groups is cardiovascular disease. In the analysis of heart function, analyzing the left ventricle (LV) from 2D echocardiographic images is a common medical procedure for heart patients. ...

Eliminating Data Duplication in CQA Platforms Using Deep Neural Model.

Computational intelligence and neuroscience
Primary research to detect duplicate question pairs within community-based question answering systems is based on datasets made of English questions only. This research put forward a solution to the problem of duplicate question detection by matching...

Insulator Leakage Current Prediction Using Hybrid of Particle Swarm Optimization and Gene Algorithm-Based Neural Network and Surface Spark Discharge Data.

Computational intelligence and neuroscience
This study proposes a new superior hybrid algorithm, which is the particle swarm optimization (PSO) and gene algorithm (GA)-based neural network to predict the leakage current of insulators. The developed algorithm was utilized for the online monitor...

Machine Learning-Based Fragility Assessment of Reinforced Concrete Buildings.

Computational intelligence and neuroscience
In the past, large earthquakes caused the collapse of infrastructure and killed thousands of people in Pakistan, a seismically active region. Therefore, the seismic assessment of infrastructure is a dire need that can be done using the fragility anal...

An Artificial Neural Network-Based Approach to Optimizing Energy Efficiency in Residential Buildings in Hot Summer and Cold Winter Regions.

Computational intelligence and neuroscience
Resource depletion and ecological crisis have prompted human beings to reflect on the behavior patterns based on industrial civilization so as to seek ways of sustainable development of human society, economy, technology, and environment. The energy ...