AIMC Topic: Deep Learning

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Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors.

Scientific reports
Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging tumor segmentation tasks is localization of pancreatic ductal adenocarcinoma (PDAC). Exclusive appl...

Cascaded 3D UNet architecture for segmenting the COVID-19 infection from lung CT volume.

Scientific reports
World Health Organization (WHO) declared COVID-19 (COronaVIrus Disease 2019) as pandemic on March 11, 2020. Ever since then, the virus is undergoing different mutations, with a high rate of dissemination. The diagnosis and prognosis of COVID-19 are c...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

Journal of healthcare engineering
This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its su...

Deep Learning-Based Fake Information Detection and Influence Evaluation.

Computational intelligence and neuroscience
With the prevalence of the Internet, a large number of users have participated in OSN (Online Social Networks), which has gradually made it the mainstream way for obtaining news or information from the Internet. However, with the rapid development of...

Application of Unsupervised Migration Method Based on Deep Learning Model in Basketball Training.

Computational intelligence and neuroscience
Nowadays, China's sports industry has attained effective development, but the athlete's efficiency in the training process is too complex to have a scientific guarantee. Machine learning technology's help in guiding the sports training process has be...

Cross-Border E-Commerce Intelligent Information Recommendation System Based on Deep Learning.

Computational intelligence and neuroscience
In order to improve the effect of cross-border e-commerce intelligent information recommendation, this paper applies deep learning to the intelligent information processing and intelligent recommendation of e-commerce and proposes an improved version...

Design of Motion Detection Device in Sports Based on Deep Learning of Internet of Things.

Computational intelligence and neuroscience
With the improvement of people's income levels in recent years, people have gradually begun to pay more attention to health, and the number of exercise and fitness people has increased year by year. People are gradually willing to pay for sports and ...

LHPE-nets: A lightweight 2D and 3D human pose estimation model with well-structural deep networks and multi-view pose sample simplification method.

PloS one
The cross-view 3D human pose estimation model has made significant progress, it better completed the task of human joint positioning and skeleton modeling in 3D through multi-view fusion method. The multi-view 2D pose estimation part of this model is...

The research of ARIMA, GM(1,1), and LSTM models for prediction of TB cases in China.

PloS one
BACKGROUND AND OBJECTIVE: Tuberculosis (Tuberculosis, TB) is a public health problem in China, which not only endangers the population's health but also affects economic and social development. It requires an accurate prediction analysis to help to m...

Model-driven deep unrolling: Towards interpretable deep learning against noise attacks for intelligent fault diagnosis.

ISA transactions
Intelligent fault diagnosis (IFD) has experienced tremendous progress owing to a great deal to deep learning (DL)-based methods over the decades. However, the "black box" nature of DL-based methods still seriously hinders wide applications in industr...