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Investigating 3D holoscopic visual content upsampling using super-resolution for cultural heritage digitization
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Elsevier B.V.
, 2019 , Article)
Through this paper, we aim at investigating the impact of using deep learning-based technologies such as super-resolution on Holoscopic 3D (H3D) images. Holoscopic 3D imaging is a technology that aims at providing ...
A Deep Learning Spatiotemporal Prediction Framework for Mobile Crowdsourced Services
(
Springer New York LLC
, 2019 , Article)
This papers presents a deep learning-based framework to predict crowdsourced service availability spatially and temporally. A novel two-stage prediction model is introduced based on historical spatio-temporal traces of ...
DLRT: Deep learning approach for reliable diabetic treatment
(
Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Diabetic therapy or insulin treatment enables patients to control the blood glucose level. Today, instead of physically utilizing syringes for infusing insulin, a patient can utilize a gadget, for example, a Wireless Insulin ...
A Deep Learning Based Automatic Severity Detector for Diabetic Retinopathy
(
Springer Verlag
, 2018 , Conference Paper)
Automated Diabetic Retinopathy (DR) screening methods with high accuracy have the strong potential to assist doctors in evaluating more patients and quickly routing those who need help to a specialist. In this work, we ...
Convolutional Autoencoder Approach for EEG Compression and Reconstruction in m-Health Systems
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In the last few years, the number of patients with chronic diseases requiring constant monitoring increased rapidly, which motivates researchers to develop scalable remote health applications. Nevertheless, the amount of ...
Content-based image retrieval with compact deep convolutional features
(
Elsevier B.V.
, 2017 , Article)
Convolutional neural networks (CNNs) with deep learning have recently achieved a remarkable success with a superior performance in computer vision applications. Most of CNN-based methods extract image features at the last ...
Fault and performance management in multi-cloud based NFV using shallow and deep predictive structures
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Institute of Electrical and Electronics Engineers Inc.
, 2017 , Conference Paper)
Deployment of Network Function Virtualization (NFV) over multiple clouds accentuates its advantages like flexibility of virtualization, proximity to customers and lower total cost of operation. However, NFV over multiple ...
Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach
(
Springer
, 2020 , Article)
© 2020, Springer-Verlag London Ltd., part of Springer Nature. Bitcoin is a decentralized cryptocurrency, which is a type of digital asset that provides the basis for peer-to-peer financial transactions based on blockchain ...
Data-driven curation, learning and analysis for inferring evolving IoT botnets in the wild
(
Association for Computing Machinery
, 2019 , Conference Paper)
The insecurity of the Internet-of-Things (IoT) paradigm continues to wreak havoc in consumer and critical infrastructure realms. Several challenges impede addressing IoT security at large, including, the lack of IoT-centric ...
Detecting Promotion Attacks in the App Market Using Neural Networks
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Article)
App markets play an important role in distributing various apps to mobile users. The app market vendors provide reputation systems to assist users in finding useful and reputable apps by ranking them. Unfortunately, there ...