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TRUST XAI: Model-Agnostic Explanations for AI With a Case Study on IIoT Security
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Article)
Despite AI’s significant growth, its “black box" nature creates challenges in generating adequate trust. Thus, it is seldom utilized as a standalone unit in IoT high-risk applications, such as critical ...
Can AI Help in Screening Viral and COVID-19 Pneumonia?
(
Institute of Electrical and Electronics Engineers Inc.
, 2020 , Article)
Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions of people worldwide. Any technological tool enabling rapid screening of the COVID-19 ...
Hierarchical Federated Learning for Collaborative IDS in IoT Applications
(
Institute of Electrical and Electronics Engineers Inc.
, 2021 , Conference Paper)
As the Internet-of-Things devices are being very widely adopted in all fields, such as smart houses, healthcare, and transportation, extremely huge amounts of data are being gathered, shared, and processed. This fact raises ...
A set of geometrical features for writer identification
(
Springer
, 2012 , Conference Paper)
Writer identification is an important field in the forensic document examination. We propose in this paper a set of geometrical features that makes it possible to characterize writers. They include directions, curvatures ...
Composition Loss for Counting, Density Map Estimation and Localization in Dense Crowds
(
Springer Verlag
, 2018 , Conference Paper)
With multiple crowd gatherings of millions of people every year in events ranging from pilgrimages to protests, concerts to marathons, and festivals to funerals; visual crowd analysis is emerging as a new frontier in ...
Construction of audio corpus of non-native English dialects -Arabs speakers
(
European Association of Geoscientists and Engineers, EAGE
, 2017 , Conference Paper)
Speech recognition for the academic and standard languages has achieved a great development, but in the face of the multiple dialects with their differences, there is still a noticeable lack of recognition rates, especially ...
Automatic signal abnormality detection using time-frequency features and machine learning: A newborn EEG seizure case study
(
Elsevier B.V.
, 2016 , Article)
Time-frequency (TF) based machine learning methodologies can improve the design of classification systems for non-stationary signals. Using selected TF distributions (TFDs), TF feature extraction is performed on multi-channel ...
Accuracy of artificial intelligence-assisted detection of Oral Squamous Cell Carcinoma: A systematic review and meta-analysis
(
Elsevier
, 2022 , Article)
Oral Squamous Cell Carcinoma (OSCC) is an aggressive tumor with a poor prognosis. Accurate and timely diagnosis is therefore essential for reducing the burden of advanced disease and improving outcomes. In this meta-analysis, ...
Pervasive AI for IoT applications: A Survey on Resource-efficient Distributed Artificial Intelligence
(
Institute of Electrical and Electronics Engineers Inc.
, 2022 , Article)
Artificial intelligence (AI) has witnessed a substantial breakthrough in a variety of Internet of Things (IoT) applications and services, spanning from recommendation systems and speech processing applications to robotics ...
A Communication Framework with Unified Efficiency and Secrecy
(
Institute of Electrical and Electronics Engineers Inc.
, 2019 , Article)
Future wireless networks are confronted with the pressure to meet the requirements of network efficiency and communication secrecy, which require a new communication framework to unify and jointly optimize efficiency and ...