AIMC Topic: Algorithms

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Novel-view X-ray projection synthesis through geometry-integrated deep learning.

Medical image analysis
X-ray imaging is a widely used approach to view the internal structure of a subject for clinical diagnosis, image-guided interventions and decision-making. The X-ray projections acquired at different view angles provide complementary information of p...

Signed network representation with novel node proximity evaluation.

Neural networks : the official journal of the International Neural Network Society
Currently, signed network representation has been applied to many fields, e.g., recommendation platforms. A mainstream paradigm of network representation is to map nodes onto a low-dimensional space, such that the node proximity of interest can be pr...

LT-FS-ID: Log-Transformed Feature Learning and Feature-Scaling-Based Machine Learning Algorithms to Predict the -Barriers for Intrusion Detection Using Wireless Sensor Network.

Sensors (Basel, Switzerland)
The dramatic increase in the computational facilities integrated with the explainable machine learning algorithms allows us to do fast intrusion detection and prevention at border areas using Wireless Sensor Networks (WSNs). This study proposed a nov...

Development of Intelligent Fault Diagnosis Technique of Rotary Machine Element Bearing: A Machine Learning Approach.

Sensors (Basel, Switzerland)
The bearing is an essential component of a rotating machine. Sudden failure of the bearing may cause an unwanted breakdown of the manufacturing plant. In this paper, an intelligent fault diagnosis technique was developed to diagnose various faults th...

Propofol Anesthesia Depth Monitoring Based on Self-Attention and Residual Structure Convolutional Neural Network.

Computational and mathematical methods in medicine
METHODS: We compare nine index values, select CNN+EEG, which has good correlation with BIS index, as an anesthesia state observation index to identify the parameters of the model, and establish a model based on self-attention and dual resistructure c...

Research on MOOC Teaching Mode in Higher Education Based on Deep Learning.

Computational intelligence and neuroscience
With the rapid development of computer technology and network technology and the widespread popularity of electronic equipment, communication among people is more dependent on the Internet. The Internet has brought great convenience to people's lives...

Forecasting Day-Ahead Electricity Metrics with Artificial Neural Networks.

Sensors (Basel, Switzerland)
As artificial neural network architectures grow increasingly more efficient in time-series prediction tasks, their use for day-ahead electricity price and demand prediction, a task with very specific rules and highly volatile dataset values, grows mo...

A Graph Neural Network Based Decentralized Learning Scheme.

Sensors (Basel, Switzerland)
As an emerging paradigm considering data privacy and transmission efficiency, decentralized learning aims to acquire a global model using the training data distributed over many user devices. It is a challenging problem since link loss, partial devic...

A Survey of Blind Modulation Classification Techniques for OFDM Signals.

Sensors (Basel, Switzerland)
Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communic...

Human Activity and Motion Pattern Recognition within Indoor Environment Using Convolutional Neural Networks Clustering and Naive Bayes Classification Algorithms.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) systems are designed to read sensor data and analyse it to classify any detected movement and respond accordingly. However, there is a need for more responsive and near real-time systems to distinguish between false a...