AIMC Topic: Neural Networks, Computer

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Industrial equipment detection algorithm under complex working conditions based on ROMS R-CNN.

PloS one
In the paper, we proposed a deep learning-based industrial equipment detection algorithm ROMS R-CNN (Rotation Occlusion Multi-Scale Region-CNN). It can solve the problem of inaccurate detection of industrial equipment under complex working conditions...

Assessment of deep convolutional neural network models for mandibular fracture detection in panoramic radiographs.

International journal of oral and maxillofacial surgery
The aim of this study was to develop automated models for the identification and detection of mandibular fractures in panoramic radiographs using convolutional neural network (CNN) algorithms. A total of 1710 panoramic radiograph images from the year...

Forecasting carbon emissions from energy consumption in Guangdong Province, China with a novel grey multivariate model.

Environmental science and pollution research international
Carbon dioxide has a significant impact on global climate change due to its natural greenhouse effect. The objective and credible forecast of carbon emissions is very important for the government to formulate and implement the corresponding emission ...

A new radionuclide identification method for low-count energy spectra with multiple radionuclides.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Radionuclide identification is to recognize the radionuclides in the environment by analyzing the energy spectrum. Rapid and accurate identification is important for nuclear security. Current radionuclide identification methods based on traditional p...

Artificial intelligence to evaluate postoperative pain based on facial expression recognition.

European journal of pain (London, England)
BACKGROUND: Pain intensity evaluation by self-report is difficult and biased in non-communicating people, which may contribute to inappropriate pain management. The use of artificial intelligence (AI) to evaluate pain intensity based on automated fac...

SE-BLTCNN: A channel attention adapted deep learning model based on PSSM for membrane protein classification.

Computational biology and chemistry
Membrane protein classification is a key to inferring the function of uncharacterized membrane protein. To get around the time-consuming and expensive biochemical experiments in the wet lab, there has been a lot of research focusing on developing fas...

Deep learning-based framework for segmentation of multiclass rib fractures in CT utilizing a multi-angle projection network.

International journal of computer assisted radiology and surgery
PURPOSE: Clinical rib fracture diagnosis via computed tomography (CT) screening has attracted much attention in recent years. However, automated and accurate segmentation solutions remain a challenging task due to the large sets of 3D CT data to deal...

Transfer of learned dynamics between different surgical robots and operative configurations.

International journal of computer assisted radiology and surgery
PURPOSE: Using the da Vinci Research Kit (dVRK), we propose and experimentally demonstrate transfer learning (Xfer) of dynamics between different configurations and robots distributed around the world. This can extend recent research using neural net...

Deep Tower Networks for Efficient Temperature Forecasting from Multiple Data Sources.

Sensors (Basel, Switzerland)
Many data related problems involve handling multiple data streams of different types at the same time. These problems are both complex and challenging, and researchers often end up using only one modality or combining them via a late fusion based app...

A Neural Network-Based Model for Predicting Saybolt Color of Petroleum Products.

Sensors (Basel, Switzerland)
Saybolt color is a standard measurement scale used to determine the quality of petroleum products and the appropriate refinement process. However, the current color measurement methods are mostly laboratory-based, thereby consuming much time and bein...