AIMC Topic: Neural Networks, Computer

Clear Filters Showing 11881 to 11890 of 31376 articles

Cybercrime: Identification and Prediction Using Machine Learning Techniques.

Computational intelligence and neuroscience
In the world of cyber age, cybercrime is spreading its root extensively. Supervised classification methods such as the support vector machine (SVM) and K-nearest neighbor (KNN) models are employed for the classification of cybercrime data. Likewise, ...

Diagnostic and prognostic EEG analysis of critically ill patients: A deep learning study.

NeuroImage. Clinical
Visual interpretation of electroencephalography (EEG) is time consuming, may lack objectivity, and is restricted to features detectable by a human. Computer-based approaches, especially deep learning, could potentially overcome these limitations. How...

A novel machine learning model for class III surgery decision.

Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie
PURPOSE: The primary purpose of this study was to develop a new machine learning model for the surgery/non-surgery decision in class III patients and evaluate the validity and reliability of this model.

Stepwise decomposition-integration-prediction framework for runoff forecasting considering boundary correction.

The Science of the total environment
Predicting river runoff accurately is of substantial significance for flood control, water resource allocation, and basin ecological dispatching. To explore the reasonable and effective application of time series decomposition in runoff forecasting, ...

KaIDA: a modular tool for assisting image annotation in deep learning.

Journal of integrative bioinformatics
Deep learning models achieve high-quality results in image processing. However, to robustly optimize parameters of deep neural networks, large annotated datasets are needed. Image annotation is often performed manually by experts without a comprehens...

Transportation Mode Detection Combining CNN and Vision Transformer with Sensors Recalibration Using Smartphone Built-In Sensors.

Sensors (Basel, Switzerland)
Transportation Mode Detection (TMD) is an important task for the Intelligent Transportation System (ITS) and Lifelog. TMD, using smartphone built-in sensors, can be a low-cost and effective solution. In recent years, many studies have focused on TMD,...

Online Self-Calibration of 3D Measurement Sensors Using a Voxel-Based Network.

Sensors (Basel, Switzerland)
Multi-sensor fusion is important in the field of autonomous driving. A basic prerequisite for multi-sensor fusion is calibration between sensors. Such calibrations must be accurate and need to be performed online. Traditional calibration methods have...

End-to-End Point Cloud Completion Network with Attention Mechanism.

Sensors (Basel, Switzerland)
We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a "simple" network, such as multilayer perceptrons (M...

Predicting Modified Fournier Index by Using Artificial Neural Network in Central Europe.

International journal of environmental research and public health
The Modified Fournier Index () is one of the indices that can assess the erosivity of rainfall. However, the implementation of the artificial neural network (ANN) for the prediction of the is still rare. In this research, climate data (monthly and y...

EpICC: A Bayesian neural network model with uncertainty correction for a more accurate classification of cancer.

Scientific reports
Accurate classification of cancers into their types and subtypes holds the key for choosing the right treatment strategy and can greatly impact patient well-being. However, existence of large-scale variations in the molecular processes driving even a...