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Academic Articles & Research Papers
Showing 12 of 12 academic articles
Xiaoting Zhong, Brian J. Gallagher, Shusen Liu, Bhavya Kailkhura et al. • npj Computational Materials
(2022)
Abstract Machine learning models are increasingly used in materials studies because of their exceptional accuracy. However, the most accurate machine learning models are usually difficult to explain. Remedies to this problem lie in explaina...
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DOI: https://doi.org/10.1038/s41524-022-00884-7
Luciano Caroprese, Eugenio Vocaturo, Ester Zumpano • Intelligent Systems with Applications
(2022)
Artificial Intelligence algorithms are powerful in performing accurate predictions, but they are often considered black boxes as they do not provide any explanation about how outputs are derived from inputs or why a decision is taken. There...
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DOI: https://doi.org/10.1016/j.iswa.2022.200109
Soumyadeep Ray, Pronaya Bhattacharya, Ebrahim A. Mattar, Abhishek Mukhopadhyay • Computational and Structural Biotechnology Journal
(2025)
This survey examines the convergence of Explainable Artificial Intelligence (XAI) and Quantum Computing (QC) toward precision medicine. We review developments from 2018 to 2025, summarizing quantum algorithms, quantum-machine-learning model...
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Open Access (DOAJ)
DOI: 10.1016/j.csbj.2025.11.031
Santhiyakumari N., Sabarinathan S., Veerakumar S., Chandraman M. et al. • Journal of Cognitive Human-Computer Interaction
(2025)
The rapid proliferation of edge computing in smart cities has enhanced real-time data processing capabilities, but it has also exposed critical vulnerabilities to sophisticated cyber threats such as zero-day attacks. Traditional signature-b...
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Open Access (DOAJ)
DOI: 10.54216/JCHCI.100201
Aditya Kuppa, Nhien‐An Le‐Khac • IEEE Transactions on Information Forensics and Security
(2021)
Machine Learning methods are playing a vital role in combating ever-evolving threats in the cybersecurity domain. Explanation methods that shed light on the decision process of black-box classifiers are one of the biggest drivers in the suc...
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DOI: https://doi.org/10.1109/tifs.2021.3117075
Gaith Rjoub, Jamal Bentahar, Omar Abdel Wahab, Rabeb Mizouni et al. • IEEE Transactions on Network and Service Management
(2023)
The “black-box” nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create mac...
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Open Access
DOI: https://doi.org/10.1109/tnsm.2023.3282740
Nicola Capuano, Giuseppe Fenza, Vincenzo Loia, Claudio Stanzione • IEEE Access
(2022)
Nowadays, Artificial Intelligence (AI) is widely applied in every area of human being’s daily life. Despite the AI benefits, its application suffer from the opacity of complex internal mechanisms and doesn’t satisfy by design the principles...
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DOI: https://doi.org/10.1109/access.2022.3204171
Sargam Yadav, Abhishek Kaushik, Kevin McDaid • Applied AI Letters
(2026)
ABSTRACT Although artificial intelligence (AI) models have demonstrated great success and efficiency in automatically countering online hate speech and misogyny, they suffer from a lack of explainability and transparency. Explainable artifi...
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Open Access (DOAJ)
DOI: 10.1002/ail2.70028
Vladyslav Yavtukhovskyi, Violeta Tretynyk • Кібернетика та комп'ютерні технології
(2025)
Introduction. Convolutional neural networks (CNNs) are a subtype of neural networks developed specifically to work with images [1]. They have achieved great success both in research and in practical applications in recent years, however, on...
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Open Access (DOAJ)
DOI: 10.34229/2707-451X.25.2.6
Shahin Atakishiyev, Mohammad Salameh, Hengshuai Yao, Randy Goebel • IEEE Access
(2024)
Autonomous driving has achieved significant milestones in research and development over the last two decades. There is increasing interest in the field as the deployment of autonomous vehicles (AVs) promises safer and more ecologically frie...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3431437
Filip Karlo Došilović, Mario Brčić, Nikica Hlupić • International Convention on Information and Communication Technology, Electronics and Microelectronics
(2018)
In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognitio...
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DOI: https://doi.org/10.23919/mipro.2018.8400040
Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee • Discover Internet of Things
(2025)
Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...
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Open Access (DOAJ)
DOI: 10.1007/s43926-025-00100-0