AIMC Topic: Probability

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Research on Network Security Situation Awareness Based on the LSTM-DT Model.

Sensors (Basel, Switzerland)
To better understand the behavior of attackers and describe the network state, we construct an LSTM-DT model for network security situation awareness, which provides risk assessment indicators and quantitative methods. This paper introduces the conce...

Lesion probability mapping in MS patients using a regression network on MR fingerprinting.

BMC medical imaging
BACKGROUND: To develop a regression neural network for the reconstruction of lesion probability maps on Magnetic Resonance Fingerprinting using echo-planar imaging (MRF-EPI) in addition to [Formula: see text], [Formula: see text], NAWM, and GM- proba...

A sensitivity analysis of probability maps in deep-learning-based anatomical segmentation.

Journal of applied clinical medical physics
PURPOSE: Deep-learning-based segmentation models implicitly learn to predict the presence of a structure based on its overall prominence in the training dataset. This phenomenon is observed and accounted for in deep-learning applications such as natu...

Improved Support Vector Machine Enabled Radial Basis Function and Linear Variants for Remote Sensing Image Classification.

Sensors (Basel, Switzerland)
Remote sensing technologies have been widely used in the contexts of land cover and land use. The image classification algorithms used in remote sensing are of paramount importance since the reliability of the result from remote sensing depends heavi...

Impact of chart image characteristics on stock price prediction with a convolutional neural network.

PloS one
Stock price prediction has long been the subject of research because of the importance of accuracy of prediction and the difficulty in forecasting. Traditionally, forecasting has involved linear models such as AR and MR or nonlinear models such as AN...

Application of stacking hybrid machine learning algorithms in delineating multi-type flooding in Bangladesh.

Journal of environmental management
Floods are among the most devastating natural hazards in Bangladesh. The country experiences multi-type floods (i.e., fluvial, flash, pluvial, and surge floods) every year. However, areas prone to multi-type floods have not yet been assessed on a nat...

A new deep learning algorithm of 12-lead electrocardiogram for identifying atrial fibrillation during sinus rhythm.

Scientific reports
Atrial fibrillation (AF) is the most prevalent arrhythmia and is associated with increased morbidity and mortality. Its early detection is challenging because of the low detection yield of conventional methods. We aimed to develop a deep learning-bas...

Identifying factors associated with roadside work zone collisions using machine learning techniques.

Accident; analysis and prevention
Identifying factors that are associated with the probability of roadside work zone collisions enables decision makers to better assess and control the risk of scheduling a particular maintenance or construction activity by modifying the characteristi...

Unsupervised multi-sense language models for natural language processing tasks.

Neural networks : the official journal of the International Neural Network Society
Existing language models (LMs) represent each word with only a single representation, which is unsuitable for processing words with multiple meanings. This issue has often been compounded by the lack of availability of large-scale data annotated with...

Cost-sensitive learning for semi-supervised hit-and-run analysis.

Accident; analysis and prevention
Hit-and-run crashes not only degrade the morality, but also result in delays of medical services provided to victims. However, class imbalance problem exists as the number of hit-and-run crashes is much smaller than that of non-hit-and-run crashes. T...