Hybrid deep convolutional neural models for iris image recognition
Sign Up to like & getrecommendations! Published in 2021 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-021-11482-y
Abstract: This paper briefly explains about the application of deep learning-based methods for biometric applications. This work attempts to solve the problem of limited availability of datasets which affects accuracy of the classifiers. This paper explores… read more here.
Keywords: hybrid deep; network; deep learning; convolutional neural ... See more keywords
Optimization and prediction of AZ91D stellite-6 coated magnesium alloy using Box Behnken design and hybrid deep belief network
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Materials Research and Technology"
DOI: 10.1016/j.jmrt.2021.09.069
Abstract: Abstract Nowadays, the utilization of magnesium (Mg) alloys is increased due to its various beneficial characters such as better thermal conductivity, minimum density, less weight, superior strength, good dimensional, stability nature, etc. They are used… read more here.
Keywords: hybrid deep; behnken design; box behnken; deep belief ... See more keywords
A hybrid deep learning model of process-build interactions in additive manufacturing
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Manufacturing Systems"
DOI: 10.1016/j.jmsy.2020.11.001
Abstract: Abstract Laser powder bed fusion (LPBF) is a technique of additive manufacturing (AM) that is often used to construct a metal object layer-by-layer. The quality of AM builds depends to a great extent on the… read more here.
Keywords: hybrid deep; learning; process; model ... See more keywords
Blind image deblurring via hybrid deep priors modeling
Sign Up to like & getrecommendations! Published in 2020 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.01.004
Abstract: Abstract Blind image deblurring is a challenging low-level vision problem which aims to restore a sharp image only from the blurry observation. Few known information makes this problem fundamentally ill-posed. Most recent works focus on… read more here.
Keywords: hybrid deep; image; deep priors; latent image ... See more keywords
Hybrid Deep Learning: An Efficient Reconnaissance and Surveillance Detection Mechanism in SDN
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3009849
Abstract: Software defined network (SDN) centralized control intelligence and network abstraction aims to facilitate applications, service deployment, programmability, innovation and ease in configuration management of the underlying networks. However, the centralized control intelligence and programmability is… read more here.
Keywords: threats attacks; deep learning; mechanism; network ... See more keywords
A Hybrid Deep Learning-Based (HYDRA) Framework for Multifault Diagnosis Using Sparse MDT Reports
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DOI: 10.1109/access.2022.3185639
Abstract: Diminishing viability of manual fault diagnosis in the increasingly complex emerging cellular network has motivated research towards artificial intelligence (AI)-based fault diagnosis using the minimization of drive test (MDT) reports. However, existing AI solutions in… read more here.
Keywords: mdt; hybrid deep; diagnosis; deep learning ... See more keywords
A Hybrid Deep Learning Approach for Bottleneck Detection in IoT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3188635
Abstract: Cloud computing is perhaps the most enticing innovation in the present figuring situation. It gives an expense-effective arrangement by diminishing the enormous forthright expense of purchasing equipment foundations and processing power. Fog computing is an… read more here.
Keywords: hybrid deep; detection; deep learning; learning approach ... See more keywords
LAD: A Hybrid Deep Learning System for Benign Paroxysmal Positional Vertigo Disorders Diagnostic
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2022.3215625
Abstract: Herein, we introduce “Look and Diagnose” (LAD), a hybrid deep learning-based system that aims to support doctors in the medical field for diagnosing effectively the Benign Paroxysmal Positional Vertigo (BPPV) disorder. Given the body postures… read more here.
Keywords: system; hybrid deep; lad hybrid; benign paroxysmal ... See more keywords
HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2022.3158897
Abstract: Synthetic digital twins based on medical data accelerate the acquisition, labelling and decision making procedure in digital healthcare. A core part of digital healthcare twins is modelbased data synthesis, which permits the generation of realistic… read more here.
Keywords: digital twins; synthesis; myocardial velocity; 3dir mvm ... See more keywords
A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2020.2967734
Abstract: Internet-of-Things (IoT) devices and applications are being deployed in our homes and workplaces. These devices often rely on continuous data collection to feed machine learning models. However, this approach introduces several privacy and efficiency challenges,… read more here.
Keywords: privacy preserving; deep learning; privacy; hybrid deep ... See more keywords
Hybrid 2-D–3-D Deep Residual Attentional Network With Structure Tensor Constraints for Spectral Super-Resolution of RGB Images
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2020.3004934
Abstract: RGB image spectral super-resolution (SSR) is a challenging task due to its serious ill-posedness, which aims at recovering a hyperspectral image (HSI) from a corresponding RGB image. In this article, we propose a novel hybrid… read more here.
Keywords: super resolution; structure; structure tensor; spectral super ... See more keywords