AIMC Topic: Neural Networks, Computer

Clear Filters Showing 12071 to 12080 of 31376 articles

Blind-Spot Collision Detection System for Commercial Vehicles Using Multi Deep CNN Architecture.

Sensors (Basel, Switzerland)
Buses and heavy vehicles have more blind spots compared to cars and other road vehicles due to their large sizes. Therefore, accidents caused by these heavy vehicles are more fatal and result in severe injuries to other road users. These possible bli...

WER-Net: A New Lightweight Wide-Spectrum Encoding and Reconstruction Neural Network Applied to Computational Spectrum.

Sensors (Basel, Switzerland)
The computational spectrometer has significant potential for portable in situ applications. Encoding and reconstruction are the most critical technical procedures. In encoding, the random mass production and selection method lacks quantitative design...

Generalisable 3D printing error detection and correction via multi-head neural networks.

Nature communications
Material extrusion is the most widespread additive manufacturing method but its application in end-use products is limited by vulnerability to errors. Humans can detect errors but cannot provide continuous monitoring or real-time correction. Existing...

IMSE: interaction information attention and molecular structure based drug drug interaction extraction.

BMC bioinformatics
BACKGROUND: Extraction of drug drug interactions from biomedical literature and other textual data is an important component to monitor drug-safety and this has attracted attention of many researchers in healthcare. Existing works are more pivoted ar...

Machine learning analysis and prediction of N, NO, and O adsorption on activated carbon and carbon molecular sieve.

Environmental science and pollution research international
This research focuses on predicting the adsorbed amount of N, O, and NO on carbon molecular sieve and activated carbon using the artificial neural network (ANN) approach. Experimental isotherm data (data set 1242) on adsorbent type, gas type, tempera...

Near infrared spectroscopy quantification based on Bi-LSTM and transfer learning for new scenarios.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
This study proposed a deep transfer learning methodology based on an improved Bi-directional Long Short-Term Memory (Bi-LSTM) network for the first time to address the near infrared spectroscopy (NIR) model transfer issue between samples. We tested i...

Graph convolutional network based virus-human protein-protein interaction prediction for novel viruses.

Computational biology and chemistry
Computational identification of human-virus protein-protein interactions (PHIs) is a worthwhile step towards understanding infection mechanisms. Analysis of the PHI networks is important for the determination of pathogenic diseases. Prediction of the...

Using artificial intelligence to avoid human error in identifying embryos: a retrospective cohort study.

Journal of assisted reproduction and genetics
PURPOSE: To determine whether convolutional neural networks (CNN) can be used to accurately ascertain the patient identity (ID) of cleavage and blastocyst stage embryos based on image data alone.

A Semi-Supervised Methodology for Fishing Activity Detection Using the Geometry behind the Trajectory of Multiple Vessels.

Sensors (Basel, Switzerland)
Automatic Identification System (AIS) messages are useful for tracking vessel activity across oceans worldwide using radio links and satellite transceivers. Such data play a significant role in tracking vessel activity and mapping mobility patterns s...

Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation.

Computational intelligence and neuroscience
To study the effect of computerized tomography (CT) images based on deep learning algorithms on the diagnosis of pulmonary nodules and the effect of radiofrequency ablation (RFA), the -shaped fully convolutional neural network (FCNN) (-Net) was enhan...