AIMC Topic: Algorithms

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Backpropagation Neural Tree.

Neural networks : the official journal of the International Neural Network Society
We propose a novel algorithm called Backpropagation Neural Tree (BNeuralT), which is a stochastic computational dendritic tree. BNeuralT takes random repeated inputs through its leaves and imposes dendritic nonlinearities through its internal connect...

Automated detection of clinical depression based on convolution neural network model.

Biomedizinische Technik. Biomedical engineering
As a common mental disorder, depression is placing an increasing burden on families and society. However, the current methods of depression detection have some limitations, and it is essential to find an objective and efficient method. With the devel...

Decision Support Systems in HF based on Deep Learning Technologies.

Current heart failure reports
PURPOSE OF REVIEW: Application of deep learning (DL) is growing in the last years, especially in the healthcare domain. This review presents the current state of DL techniques applied to electronic health record structured data, physiological signals...

Aircraft Landing Gear Retraction/Extension System Fault Diagnosis with 1-D Dilated Convolutional Neural Network.

Sensors (Basel, Switzerland)
The faults of the landing gear retraction/extension(R/E) system can result in the deterioration of an aircraft's maneuvering conditions; how to identify the faults of the landing gear R/E system has become a key issue for ensuring aircraft take-off a...

Cross-Modal Object Detection Based on a Knowledge Update.

Sensors (Basel, Switzerland)
As an important field of computer vision, object detection has been studied extensively in recent years. However, existing object detection methods merely utilize the visual information of the image and fail to mine the high-level semantic informatio...

Mechanism Analysis and Self-Adaptive RBFNN Based Hybrid Soft Sensor Model in Energy Production Process: A Case Study.

Sensors (Basel, Switzerland)
Despite hard sensors can be easily used in various condition monitoring of energy production process, soft sensors are confined to some specific scenarios due to difficulty installation requirements and complex work conditions. However, industrial pr...

A feasibility study for in vivo treatment verification of IMRT using Monte Carlo dose calculation and deep learning-based modelling of EPID detector response.

Radiation oncology (London, England)
BACKGROUND: This paper describes the development of a predicted electronic portal imaging device (EPID) transmission image (TI) using Monte Carlo (MC) and deep learning (DL). The measured and predicted TI were compared for two-dimensional in vivo rad...

Diabetes mellitus risk prediction in the presence of class imbalance using flexible machine learning methods.

BMC medical informatics and decision making
BACKGROUND: Early detection and prediction of type two diabetes mellitus incidence by baseline measurements could reduce associated complications in the future. The low incidence rate of diabetes in comparison with non-diabetes makes accurate predict...

Intrinsic Decomposition Method Combining Deep Convolutional Neural Network and Probability Graph Model.

Computational intelligence and neuroscience
With the rapid development of computer vision and artificial intelligence, people are increasingly demanding image decomposition. Many of the current methods do not decompose images well. In order to find the decomposition method with high accuracy a...

Investigation of Three-Dimensional Condensation Film Problem over an Inclined Rotating Disk Using a Nonlinear Autoregressive Exogenous Model.

Computational intelligence and neuroscience
This paper analyzed the three-dimensional (3D) condensation film problem over an inclined rotating disk. The mathematical model of the problem is governed by nonlinear partial differential equations (NPDE's), which are reduced to the system of nonlin...