AIMC Topic: Neural Networks, Computer

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GADF-VGG16 based fault diagnosis method for HVDC transmission lines.

PloS one
Transmission lines are most prone to faults in the transmission system, so high-precision fault diagnosis is very important for quick troubleshooting. There are some problems in current intelligent fault diagnosis research methods, such as difficulty...

2D Transformations of Energy Signals for Energy Disaggregation.

Sensors (Basel, Switzerland)
The aim of Non-Intrusive Load Monitoring is to estimate the energy consumption of individual electrical appliances by disaggregating the overall power consumption that has been sampled from a smart meter at a house or commercial/industrial building. ...

Utility of the deep learning technique for the diagnosis of orbital invasion on CT in patients with a nasal or sinonasal tumor.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: In nasal or sinonasal tumors, orbital invasion beyond periorbita by the tumor is one of the important criteria in the selection of the surgical procedure. We investigated the usefulness of the convolutional neural network (CNN)-based deep...

A pipeline for automated deep learning liver segmentation (PADLLS) from contrast enhanced CT exams.

Scientific reports
Multiple studies have created state-of-the-art liver segmentation models using Deep Convolutional Neural Networks (DCNNs) such as the V-net and H-DenseUnet. Oversegmentation however continues to be a problem. We set forth to address these limitations...

Green Financial Health Risk Early Monitoring of Commercial Banks Based on Neural Network Model in a Small Sample Environment.

Journal of environmental and public health
Financial innovations emerge in an endless stream, and it is difficult for the regulatory measures and efforts of banks in various countries and the credit risk management level of commercial banks themselves to adapt to the increasingly complex risk...

Digital Media Teaching and Effectiveness Evaluation Integrating Big Data and Artificial Intelligence.

Computational intelligence and neuroscience
With the development of digital media technology, its application in teaching and learning is becoming more widespread. Digital media technology helps present information in transmitting knowledge or skills, reduces cognitive load, and promotes under...

The Evaluation on the Credit Risk of Enterprises with the CNN-LSTM-ATT Model.

Computational intelligence and neuroscience
Credit evaluation is a difficult problem in the process of financing and loan for small and medium-sized enterprises. Due to the high dimension and nonlinearity of enterprise behavior data, traditional logistic regression (LR), random forest (RF), an...

Mapping artisanal and small-scale mines at large scale from space with deep learning.

PloS one
Artisanal and small-scale mines (asm) are on the rise. They represent a crucial source of wealth for numerous communities but are rarely monitored or regulated. The main reason being the unavailability of reliable information on the precise location ...

Towards annotation-efficient segmentation via image-to-image translation.

Medical image analysis
An important challenge and limiting factor in deep learning methods for medical imaging segmentation is the lack of available of annotated data to properly train models. For the specific task of tumor segmentation, the process entails clinicians labe...

A novel P-QRS-T wave localization method in ECG signals based on hybrid neural networks.

Computers in biology and medicine
As the number of people suffering from cardiovascular diseases increases every year, it becomes essential to have an accurate automatic electrocardiogram (ECG) diagnosis system. Researchers have adopted different methods, such as deep learning, to in...