AIMC Topic: Neural Networks, Computer

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Proposed algorithm for smart grid DDoS detection based on deep learning.

Neural networks : the official journal of the International Neural Network Society
The Smart Grid's objective is to increase the electric grid's dependability, security, and efficiency through extensive digital information and control technology deployment. As a result, it is necessary to apply real-time analysis and state estimati...

Generating new protein sequences by using dense network and attention mechanism.

Mathematical biosciences and engineering : MBE
Protein engineering uses de novo protein design technology to change the protein gene sequence, and then improve the physical and chemical properties of proteins. These newly generated proteins will meet the needs of research better in properties and...

Intelligent Reflecting Surface-Assisted Physical Layer Key Generation with Deep Learning in MIMO Systems.

Sensors (Basel, Switzerland)
Physical layer secret key generation (PLKG) is a promising technology for establishing effective secret keys. Current works for PLKG mostly study key generation schemes in ideal communication environments with little or even no signal interference. I...

RUC-Net: A Residual-Unet-Based Convolutional Neural Network for Pixel-Level Pavement Crack Segmentation.

Sensors (Basel, Switzerland)
Automatic crack detection is always a challenging task due to the inherent complex backgrounds, uneven illumination, irregular patterns, and various types of noise interference. In this paper, we proposed a U-shaped encoder-decoder semantic segmentat...

An Efficient Dehazing Algorithm Based on the Fusion of Transformer and Convolutional Neural Network.

Sensors (Basel, Switzerland)
The purpose of image dehazing is to remove the interference from weather factors in degraded images and enhance the clarity and color saturation of images to maximize the restoration of useful features. Single image dehazing is one of the most import...

Development of Machine Learning Model for Prediction of Demolition Waste Generation Rate of Buildings in Redevelopment Areas.

International journal of environmental research and public health
Owing to a rapid increase in waste, waste management has become essential, for which waste generation (WG) information has been effectively utilized. Various studies have recently focused on the development of reliable predictive models by applying a...

Construction of a machine learning-based artificial neural network for discriminating PANoptosis related subgroups to predict prognosis in low-grade gliomas.

Scientific reports
The poor prognosis of gliomas necessitates the search for biomarkers for predicting clinical outcomes. Recent studies have shown that PANoptosis play an important role in tumor progression. However, the role of PANoptosis in in gliomas has not been f...

Convolutional neural network for automated segmentation of the liver and its vessels on non-contrast T1 vibe Dixon acquisitions.

Scientific reports
We evaluated the effectiveness of automated segmentation of the liver and its vessels with a convolutional neural network on non-contrast T1 vibe Dixon acquisitions. A dataset of non-contrast T1 vibe Dixon liver magnetic resonance images was labelled...

Classification at the accuracy limit: facing the problem of data ambiguity.

Scientific reports
Data classification, the process of analyzing data and organizing it into categories or clusters, is a fundamental computing task of natural and artificial information processing systems. Both supervised classification and unsupervised clustering wor...

Abdomen CT multi-organ segmentation using token-based MLP-Mixer.

Medical physics
BACKGROUND: Manual contouring is very labor-intensive, time-consuming, and subject to intra- and inter-observer variability. An automated deep learning approach to fast and accurate contouring and segmentation is desirable during radiotherapy treatme...