34   Artículos

 
en línea
Yifei Wang, Shiyang Chen, Guobin Chen, Ethan Shurberg, Hang Liu and Pengyu Hong    
This work considers the task of representation learning on the attributed relational graph (ARG). Both the nodes and edges in an ARG are associated with attributes/features allowing ARGs to encode rich structural information widely observed in real appli... ver más
Revista: Informatics    Formato: Electrónico

 
en línea
Abrar Alamr and Abdelmonim Artoli    
Anomaly detection is one of the basic issues in data processing that addresses different problems in healthcare sensory data. Technology has made it easier to collect large and highly variant time series data; however, complex predictive analysis models ... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Nurgali Kadyrbek, Madina Mansurova, Adai Shomanov and Gaukhar Makharova    
This study is devoted to the transcription of human speech in the Kazakh language in dynamically changing conditions. It discusses key aspects related to the phonetic structure of the Kazakh language, technical considerations in collecting the transcribe... ver más
Revista: Big Data and Cognitive Computing    Formato: Electrónico

 
en línea
Mohammed Madiafi, Jamal Ezzahar, Kamal Baraka and Abdelaziz Bouroumi    
In this paper, we propose a new neural architecture for object classification, made up from a set of competitive layers whose number and size are dynamically learned from training data using a two-step process that combines unsupervised and supervised le... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Augusto Montisci and Maria Cristina Porcu    
The proposed method is a neural-network-based tool for the early warning of ground settlement hazard in urban areas. On the basis of the analysis of MT-InSAR data through an unsupervised learning, the method can find precursors of similar time-evolving p... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Hussein Abdel-Jaber, Disha Devassy, Azhar Al Salam, Lamya Hidaytallah and Malak EL-Amir    
Deep learning uses artificial neural networks to recognize patterns and learn from them to make decisions. Deep learning is a type of machine learning that uses artificial neural networks to mimic the human brain. It uses machine learning methods such as... ver más
Revista: Algorithms    Formato: Electrónico

 
en línea
Shunlei Li, Muhammad Adeel Azam, Ajay Gunalan and Leonardo S. Mattos    
Optical coherence tomography (OCT) is a rapidly evolving imaging technology that combines a broadband and low-coherence light source with interferometry and signal processing to produce high-resolution images of living tissues. However, the speckle noise... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Shang-Yuan Chen, Tzu-Tien Chen     Pág. 146 - 156
Since dockless sharing bicycles have become an indispensable means of everyday life for urban residents, how to effectively control the supply and demand balance of bikes has become an important issue. This study aims to apply Kernel Density Estimation b... ver más
Revista: Advances in Technology Innovation    Formato: Electrónico

 
en línea
Francisco Silva, Tania Pereira, Julieta Frade, José Mendes, Claudia Freitas, Venceslau Hespanhol, José Luis Costa, António Cunha and Hélder P. Oliveira    
Lung cancer late diagnosis has a large impact on the mortality rate numbers, leading to a very low five-year survival rate of 5%. This issue emphasises the importance of developing systems to support a diagnostic at earlier stages. Clinicians use Compute... ver más
Revista: Applied Sciences    Formato: Electrónico

 
en línea
Nishant Kumar and Stefan Gumhold    
Image fusion helps in merging two or more images to construct a more informative single fused image. Recently, unsupervised learning-based convolutional neural networks (CNN) have been used for different types of image-fusion tasks such as medical image ... ver más
Revista: Computers    Formato: Electrónico

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