Search Results for author: Mohamed Reda Bouadjenek

Found 15 papers, 1 papers with code

Data Quality in Edge Machine Learning: A State-of-the-Art Survey

no code implementations1 Jun 2024 Mohammed Djameleddine Belgoumri, Mohamed Reda Bouadjenek, Sunil Aryal, Hakim Hacid

From these observations, it follows that DQ research for edge ML is a critical and urgent exploration track for the safety and robust usefulness of present and future AI systems.

Autonomous Driving Edge-computing +2

Data-driven Machinery Fault Detection: A Comprehensive Review

no code implementations29 May 2024 Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal

With the massive surge in industrial big data and advancement in sensing and computational technologies, data-driven Machinery Fault Diagnosis (MFD) solutions based on machine/deep learning approaches have been used ubiquitously in manufacturing.

Fault Detection

Review for Handling Missing Data with special missing mechanism

no code implementations7 Apr 2024 Youran Zhou, Sunil Aryal, Mohamed Reda Bouadjenek

Understanding what missing data is, how it occurs, and why it is crucial to handle it appropriately is paramount when working with real-world data, especially in tabular data, one of the most commonly used data types in the real world.

Decision Making Imputation

The Pursuit of Fairness in Artificial Intelligence Models: A Survey

no code implementations26 Mar 2024 Tahsin Alamgir Kheya, Mohamed Reda Bouadjenek, Sunil Aryal

This survey offers a synopsis of the different ways researchers have promoted fairness in AI systems.


Hierarchical Classification for Intrusion Detection System: Effective Design and Empirical Analysis

no code implementations17 Mar 2024 Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek, Muna Al-Hawawreh, Md. Alamin Talukder

With the increased use of network technologies like Internet of Things (IoT) in many real-world applications, new types of cyberattacks have been emerging.

Classification Intrusion Detection +1

usfAD Based Effective Unknown Attack Detection Focused IDS Framework

no code implementations17 Mar 2024 Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek, Muna Al-Hawawreh, Md. Alamin Talukder

To address this challenge, we put forth two strategies for semi-supervised learning based IDS where training samples of attacks are not required: 1) training a supervised machine learning model using randomly and uniformly dispersed synthetic attack samples; 2) building a One Class Classification (OCC) model that is trained exclusively on benign network traffic.

Intrusion Detection One-Class Classification

Training Machine Learning models at the Edge: A Survey

no code implementations5 Mar 2024 Aymen Rayane Khouas, Mohamed Reda Bouadjenek, Hakim Hacid, Sunil Aryal

This survey delves into Edge Learning (EL), specifically the optimization of ML model training at the edge.

Edge-computing Federated Learning

SHINE: Deep Learning-Based Accessible Parking Management System

no code implementations2 Feb 2023 Dhiraj Neupane, Aashish Bhattarai, Sunil Aryal, Mohamed Reda Bouadjenek, Uk-Min Seok, Jongwon Seok

However, this gradual increment in the number of vehicles has inevitably led to parking-related issues, including the abuse of disabled parking spaces (hereafter referred to as accessible parking spaces) designated for individuals with disabilities.

License Plate Recognition Management +2

Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey

no code implementations22 Feb 2022 Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak, Kevin Lee, Chetan Arora, Ali Hassani, Arkady Zaslavsky

Indeed, Adversarial Artificial Intelligence (AI) which refers to a set of techniques that attempt to fool machine learning models with deceptive data, is a growing threat in the AI and machine learning research community, in particular for machine-critical applications.

Adversarial Attack BIG-bench Machine Learning +3

Unintended Bias in Language Model-driven Conversational Recommendation

no code implementations17 Jan 2022 Tianshu Shen, Jiaru Li, Mohamed Reda Bouadjenek, Zheda Mai, Scott Sanner

Conversational Recommendation Systems (CRSs) have recently started to leverage pretrained language models (LM) such as BERT for their ability to semantically interpret a wide range of preference statement variations.

Language Modelling Recommendation Systems

Feature Extraction Functions for Neural Logic Rule Learning

no code implementations14 Aug 2020 Shashank Gupta, Antonio Robles-Kelly, Mohamed Reda Bouadjenek

Combining symbolic human knowledge with neural networks provides a rule-based ante-hoc explanation of the output.

Sentiment Analysis Sentiment Classification

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