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Deep learning and low rank dictionary model for mHealth data classification
(
Institute of Electrical and Electronics Engineers Inc.
, 2018 , Conference Paper)
In the context of mobile Health (mHealth) applications, data are prone to several sources of contamination which would lead to false interpretation and misleading classification results. In this paper, a robust deep learning ...
RF-based drone detection and identification using deep learning approaches: An initiative towards a large open source drone database
(
Elsevier B.V.
, 2019 , Article)
The omnipresence of unmanned aerial vehicles, or drones, among civilians can lead to technical, security, and public safety issues that need to be addressed, regulated and prevented. Security agencies are in continuous ...
Glandular structure-guided classification of microscopic colorectal images using deep learning
(
Elsevier Ltd
, 2019 , Article)
In this work, we propose to automate the pre-cancerous tissue abnormality analysis by performing the classification of image patches using a novel two-stage convolutional neural network (CNN) based framework. Rather than ...
Fault and performance management in multi-cloud virtual network services using AI: A tutorial and a case study
(
Elsevier B.V.
, 2019 , Article)
Carriers find Network Function Virtualization (NFV) and multi-cloud computing a potent combination for deploying their network services. The resulting virtual network services (VNS) offer great flexibility and cost advantages ...
A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models
(
Association for Computational Linguistics (ACL)
, 2017 , Conference Paper)
Opinion mining in Arabic is a challenging task given the rich morphology of the language. The task becomes more challenging when it is applied to Twitter data, which contains additional sources of noise, such as the use ...
Deep learning models for sentiment analysis in arabic
(
Association for Computational Linguistics (ACL)
, 2015 , Conference Paper)
In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input ...
Investigating 3D holoscopic visual content upsampling using super-resolution for cultural heritage digitization
(
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 ...
The research on detection of crop diseases ranking based on transfer learning
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Crop diseases are a major global threat to food security. Because the lack of agriculture experts or necessary facilities, it is difficult to determine the type of disease, as well as the degree of disease in time, which ...
Digital heritage enrichment through artificial intelligence and semanticweb technologies
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Conference Paper)
Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments ...
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 ...