Comprehensive Exploration of Target‐specific Ligands Using a Graph Convolution Neural Network
Sign Up to like & getrecommendations! Published in 2019 at "Molecular Informatics"
DOI: 10.1002/minf.201900095
Abstract: Machine learning approaches are widely used to evaluate ligand activities of chemical compounds toward potential target proteins. Especially, exploration of highly selective ligands is important for the development of new drugs with higher safety. One… read more here.
Keywords: convolution neural; graph convolution; exploration; target ... See more keywords
Near-surface PM2.5 prediction combining the complex network characterization and graph convolution neural network
Sign Up to like & getrecommendations! Published in 2021 at "Neural Computing and Applications"
DOI: 10.1007/s00521-021-06300-3
Abstract: Massive studies focus on the prediction of main pollutants, to improve air quality by revealing the evolution of pollutants. However, existing prediction methods mostly emphasize the fitting analysis of time series, but ignore the spatial… read more here.
Keywords: convolution neural; network; graph convolution; neural network ... See more keywords
An efficient categorization of liver cirrhosis using convolution neural networks for health informatics
Sign Up to like & getrecommendations! Published in 2017 at "Cluster Computing"
DOI: 10.1007/s10586-017-1629-2
Abstract: Accurate categorization of cirrhosis liver image in ultrasound modality is of great importance in medical diagnosis and treatment. Health informatics is important as it provides quick predictions on diseases based on nearness of symptoms. Modelling… read more here.
Keywords: categorization; image; convolution neural; cirrhosis ... See more keywords
Two open-source projects for image aesthetic quality assessment
Sign Up to like & getrecommendations! Published in 2018 at "Science China Information Sciences"
DOI: 10.1007/s11432-018-9692-2
Abstract: Here we introduce two open-source projects for image aesthetic quality assessment. The first one is ILGnet, an open-source project for the aesthetic evaluation of images based on the convolution neural network. The second is CJS-CNN,… read more here.
Keywords: aesthetic quality; image; convolution neural; image aesthetic ... See more keywords
Convolution neural networks for real-time needle detection and localization in 2D ultrasound
Sign Up to like & getrecommendations! Published in 2018 at "International Journal of Computer Assisted Radiology and Surgery"
DOI: 10.1007/s11548-018-1721-y
Abstract: PurposeWe propose a framework for automatic and accurate detection of steeply inserted needles in 2D ultrasound data using convolution neural networks. We demonstrate its application in needle trajectory estimation and tip localization.MethodsOur approach consists of… read more here.
Keywords: detection; convolution neural; neural networks; time ... See more keywords
Extraction of road blockage information for the Jiuzhaigou earthquake based on a convolution neural network and very-high-resolution satellite images
Sign Up to like & getrecommendations! Published in 2019 at "Earth Science Informatics"
DOI: 10.1007/s12145-019-00413-z
Abstract: Road blockage information extraction from a single-phase postdisaster image is difficult because roads are narrow and easily covered by vegetation. The traditional object-oriented image analysis method is restrictive, and its detection is slow. A deep… read more here.
Keywords: blockage information; road blockage; road; convolution neural ... See more keywords
Deep convolution neural network based approach for multispectral images
Sign Up to like & getrecommendations! Published in 2021 at "International Journal of Systems Assurance Engineering and Management"
DOI: 10.1007/s13198-021-01133-8
Abstract: In this paper, we propose an effective image fusion technique employing a deep learning framework. The novelty of the project is to process image fusion to collect utmost information that is potential. We tend to… read more here.
Keywords: neural network; image fusion; image; convolution neural ... See more keywords
A deep hybrid learning model to detect unsafe behavior: Integrating convolution neural networks and long short-term memory
Sign Up to like & getrecommendations! Published in 2018 at "Automation in Construction"
DOI: 10.1016/j.autcon.2017.11.002
Abstract: Abstract Computer vision and pattern recognition approaches have been applied to determine unsafe behaviors on construction sites. Such approaches have been reliant on the computation of artificially complex image features that utilize a cumbersome parameter… read more here.
Keywords: unsafe actions; convolution neural; long short; model ... See more keywords
iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components.
Sign Up to like & getrecommendations! Published in 2019 at "Journal of theoretical biology"
DOI: 10.1016/j.jtbi.2018.12.034
Abstract: The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl group. This methylation process is a post-transcriptional modification, which… read more here.
Keywords: methylation sites; methylation; convolution neural; pseknc 2methyl ... See more keywords
Ship Type Recognition via a Coarse-to-Fine Cascaded Convolution Neural Network
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Navigation"
DOI: 10.1017/s0373463319000900
Abstract: Most previous research has handled the task of ship type recognition by exploring hand-craft ship features, which may fail to distinguish ships with similar visual appearances. This situation motivates us to propose a novel deep… read more here.
Keywords: ship; ship type; type recognition; coarse fine ... See more keywords
Intelligent convolution neural network-assisted SERS to realize highly accurate identification of six pathogenic Vibrio.
Sign Up to like & getrecommendations! Published in 2023 at "Chemical communications"
DOI: 10.1039/d3cc01129a
Abstract: Based on label-free SERS technology, the relationship between the Raman signals of pathogenic Vibrio microorganisms and purine metabolites was analyzed in detail. A deep learning CNN model was successfully developed, achieving a high accuracy rate… read more here.
Keywords: convolution neural; identification six; pathogenic vibrio; vibrio ... See more keywords