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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 ...
Machine learning-based management of electric vehicles charging: Towards highly-dispersed fast chargers
(
MDPI AG
, 2020 , Article)
Coordinated charging of electric vehicles (EVs) improves the overall efficiency of the power grid as it avoids distribution system overloads, increases power quality, and decreases voltage fluctuations. Moreover, the ...
Video surveillance using deep transfer learning and deep domain adaptation: Towards better generalization
(
Elsevier
, 2023 , Other)
Recently, developing automated video surveillance systems (VSSs) has become crucial to ensure the security and safety of the population, especially during events involving large crowds, such as sporting events. While ...
WSNet - Convolutional Neural Networkbased Word Spotting for Arabic and English Handwritten Documents
(
UIKTEN - Association for Information Communication Technology Education and Science
, 2022 , Article)
This paper proposes a new convolutional neural network architecture to tackle the problem of word spotting in handwritten documents. A Deep learning approach using a novel Convolutional Neural Network is developed for the ...
Reinforcement learning approaches for efficient and secure blockchain-powered smart health systems
(
Elsevier B.V.
, 2021 , Article)
Emerging technological innovation toward e-Health transition is a worldwide priority for ensuring people's quality of life. Hence, secure exchange and analysis of medical data amongst diverse organizations would increase ...
Deep Reinforcement Learning Algorithm for Smart Data Compression under NOMA-Uplink Protocol
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Conference Paper)
One of the highly promising radio access strategies for enhancing performance in the next generation cellular communications is non-orthogonal multiple access (NOMA). NOMA offers a number of advantages including better ...
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 ...
A New Deep Learning Method for Accurate Cardiac Heart Failure Prediction from RR Interval Measurements
(
IEEE
, 2022 , Conference Paper)
cardiovascular diseases are the major cause of death worldwide. Early detection of heart failure will assist patients and medical professionals in taking better precautions to reduce risks. The objective of this study is ...
Multi-scale-based Network for Image Dehazing
(
Institute of Electrical and Electronics Engineers Inc. (IEEE)
, 2023 , Article)
Image and video dehazing is a difficult subject that has received a lot of attention in the field of computer vision. The presence of air haze in photos and movies can reduce visual quality dramatically, resulting in a ...
A meta-framework for modeling the human reading process in sentiment analysis
(
Association for Computing Machinery
, 2016 , Article)
This article introduces a sentiment analysis approach that adopts the way humans read, interpret, and extract sentiment from text. Our motivation builds on the assumption that human interpretation should lead to the most ...